Main.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zd24fN5dAkSw"
   },
   "source": [
    "### **1. SVM on original dataset with various feature representation techniques :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "t48pHobshiLi"
   },
   "outputs": [],
   "source": [
    "# Import required libraries\n",
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n",
    "from sklearn import svm\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import normalize\n",
    "from sklearn.metrics import accuracy_score, classification_report, plot_roc_curve, homogeneity_completeness_v_measure, silhouette_score\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "f9GXmgh2DaoU"
   },
   "outputs": [],
   "source": [
    "#defining dataset paths\n",
    "B_path = '/content/App Dataset/Dataset/B/sys'\n",
    "M_path = '/content/App Dataset/Dataset/M/sys'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HtkGnc47Ca6Y"
   },
   "source": [
    "**Model Based on Occurence of Calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "HFEGFWprKK8B"
   },
   "outputs": [],
   "source": [
    "#function to calculate model metrics and plot results and ROC curve\n",
    "def model(kernel, train_x, train_y, test_x, test_y):\n",
    "  clf = svm.SVC(kernel = kernel)\n",
    "  clf.fit(train_x, train_y)\n",
    "  pred = clf.predict(test_x)\n",
    "  metrics = classification_report(test_y, pred, target_names = ['B','M'])[:168]\n",
    "  acc = accuracy_score(test_y, pred)\n",
    "  plot_roc_curve(clf, test_x, test_y)\n",
    "  plt.title(\"kernel : {}\".format(kernel))\n",
    "  plt.show()\n",
    "  print('\\033[1m'+'\\n{} \\n Accuracy : {} \\n'.format(metrics,acc)+'\\033[0m')  \n",
    "  return acc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "UA6TSPBrmd3s"
   },
   "outputs": [],
   "source": [
    "#fucntion to read data from the file provided\n",
    "def corp(path, label):\n",
    "  os.chdir(path)\n",
    "  corpus = []\n",
    "  for file in os.listdir(): \n",
    "      file1 = open(file,\"r\")\n",
    "      calls = file1.read()\n",
    "      calls = calls.replace('\\n',' ')[:-1]\n",
    "      call_list = (calls, label)\n",
    "      corpus.append(call_list)\n",
    "  return corpus"
   ]
  },
  {
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    "id": "g7Byi9hZmd3w",
    "outputId": "8ededf88-c055-4bba-e14b-660779aba48a"
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Calls</th>\n",
       "      <th>Class</th>\n",
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       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
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      "text/plain": [
       "                                                                                                Calls  Class\n",
       "com.foodiestrip.apk.sys_names.txt                   ioctl ioctl clock_gettime clock_gettime clock_...      0\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                 writev ioctl getuid epoll_pwait epoll_ctl recv...      0\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...  getuid writev write mprotect faccessat newfsta...      0\n",
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       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt  getuid epoll_pwait read recvfrom sendto recvfr...      0"
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     },
     "execution_count": 6,
     "metadata": {
      "tags": []
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     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting dataset from B directory\n",
    "df_B = pd.DataFrame(corp(B_path,0), columns = ['Calls', 'Class'])\n",
    "df_B.index = os.listdir(B_path)\n",
    "df_B.head()"
   ]
  },
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       "                                                                                                Calls  Class\n",
       "d3b5934d22b1e58f62b56d15653964f5161f421eaa68da0...  munmap close openat fstat close openat fstat c...      1\n",
       "32fe9ef7ee7f2214d686a88e9be101a74cc9b1ab47f52d7...  recvfrom recvfrom recvfrom recvfrom recvfrom r...      1\n",
       "4d873af4820deacba019f177b37f13495910568bf3547b8...  pread pread mmap munmap pread pread mmap munma...      1\n",
       "62579a46b244d2f91550736dbb6a7f2b1896106424f8c4f...  read getuid epoll_pwait ioctl getuid epoll_pwa...      1\n",
       "66e9f7ac68fb07aec08d9fcefbeec04e0d10702d335ac6a...  ioctl ioctl faccessat mprotect mprotect mprote...      1"
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     "execution_count": 7,
     "metadata": {
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   ],
   "source": [
    "#getting dataset from M directory\n",
    "df_M = pd.DataFrame(corp(M_path,1), columns = ['Calls', 'Class'])\n",
    "df_M.index = os.listdir(M_path)\n",
    "df_M.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "yOcD7Skjmd32"
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   "outputs": [],
   "source": [
    "df = df_B.append([df_M])                #joining the above dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "NE-rxB0Fmd33"
   },
   "outputs": [],
   "source": [
    "#Using CountVectorizer method from sklearn library \n",
    "vectorizer = CountVectorizer()          \n",
    "X = vectorizer.fit_transform(df.Calls)"
   ]
  },
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       "      <td>2346</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>116</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>8478</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>327</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>521</td>\n",
       "      <td>1</td>\n",
       "      <td>2875</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>1751</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>636</td>\n",
       "      <td>686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>94</td>\n",
       "      <td>7624</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>760</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>377</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1955</td>\n",
       "      <td>0</td>\n",
       "      <td>5621</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>3140</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5712</td>\n",
       "      <td>564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>102</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>5910</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>836</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>0</td>\n",
       "      <td>2931</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2435</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>834</td>\n",
       "      <td>599</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 102 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    _llseek  ...  writev\n",
       "com.foodiestrip.apk.sys_names.txt                         0  ...     585\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                       0  ...     157\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...        0  ...     686\n",
       "com.germany.usedcars.apk.sys_names.txt                    0  ...     564\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt        0  ...     599\n",
       "\n",
       "[5 rows x 102 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Preparing a dataframe by applying the vectorizer method to the dataset\n",
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "BoCdHeNFmd37",
    "outputId": "5d4f9799-2bdf-4d6f-dd25-04c91bf1d2a1"
   },
   "outputs": [
    {
     "data": {
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       "      <th>pwrite</th>\n",
       "      <th>pwrite64</th>\n",
       "      <th>read</th>\n",
       "      <th>readlinkat</th>\n",
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       "      <th>rt_sigprocmask</th>\n",
       "      <th>rt_sigreturn</th>\n",
       "      <th>sched_getparam</th>\n",
       "      <th>sched_getscheduler</th>\n",
       "      <th>sched_yield</th>\n",
       "      <th>sendmsg</th>\n",
       "      <th>sendto</th>\n",
       "      <th>setpriority</th>\n",
       "      <th>setrlimit</th>\n",
       "      <th>setsockopt</th>\n",
       "      <th>shutdown</th>\n",
       "      <th>sigaction</th>\n",
       "      <th>sigreturn</th>\n",
       "      <th>socket</th>\n",
       "      <th>socketpair</th>\n",
       "      <th>stat64</th>\n",
       "      <th>statfs</th>\n",
       "      <th>statfs64</th>\n",
       "      <th>tgkill</th>\n",
       "      <th>tkill</th>\n",
       "      <th>ugetrlimit</th>\n",
       "      <th>uname</th>\n",
       "      <th>unlinkat</th>\n",
       "      <th>utimensat</th>\n",
       "      <th>wait4</th>\n",
       "      <th>write</th>\n",
       "      <th>writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26254</td>\n",
       "      <td>8</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "      <td>110</td>\n",
       "      <td>4975</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>158</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2228</td>\n",
       "      <td>0</td>\n",
       "      <td>4985</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2746</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2581</td>\n",
       "      <td>585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>312</td>\n",
       "      <td>0</td>\n",
       "      <td>123</td>\n",
       "      <td>0</td>\n",
       "      <td>338</td>\n",
       "      <td>3173</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>129</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>178</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1063</td>\n",
       "      <td>0</td>\n",
       "      <td>3727</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>684</td>\n",
       "      <td>3</td>\n",
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       "      <td>2913</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2346</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>116</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>8478</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>327</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>521</td>\n",
       "      <td>1</td>\n",
       "      <td>2875</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>1751</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>636</td>\n",
       "      <td>686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>157</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>94</td>\n",
       "      <td>7624</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>760</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>377</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1955</td>\n",
       "      <td>0</td>\n",
       "      <td>5621</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>3140</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5712</td>\n",
       "      <td>564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>102</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>5910</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>836</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>0</td>\n",
       "      <td>2931</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2435</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>834</td>\n",
       "      <td>599</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...     585\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...     157\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...     686\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...     564\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...     599\n",
       "\n",
       "[5 rows x 103 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Preparing the final dataset\n",
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "g4xjIIGXH7I1"
   },
   "source": [
    "**SVM Models :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Kizk8NmPZJJI"
   },
   "outputs": [],
   "source": [
    "#Splitting the dataset into train and test data\n",
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "x = normalize(x)\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "8bySagcIfYjE",
    "outputId": "a4e123f1-c16a-4463-b651-f484ae3e16cf"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.92      0.92       251\n",
      "           M       0.94      0.95      0.94       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9331046312178388 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "#Calling the model function for model metrics and plotting\n",
    "acc1_occ = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "V-pfncM1RT2X",
    "outputId": "eddd4cab-354e-48c1-b141-b8f3b5462b0c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.91      0.92      0.91       251\n",
      "           M       0.94      0.93      0.93       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9228130360205832 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_occ = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "5PVpT5h7RWNU",
    "outputId": "c410c3d2-bee7-4080-9fab-40062349f24a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.95      0.92      0.94       251\n",
      "           M       0.94      0.97      0.95       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9468267581475128 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_occ = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "a46SQaIJwA5Q"
   },
   "source": [
    "**Model based on Boolean occurence of calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "m_T-uaxq6I6k",
    "outputId": "69ff134e-81b6-4eb9-d074-4440faa11eaa"
   },
   "outputs": [
    {
     "data": {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...       1\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...       1\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...       1\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...       1\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...       1\n",
       "\n",
       "[5 rows x 103 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Preparing Boolean Occurence dataset from the above dataset by setting values as 1 where count > 1 \n",
    "for i in df_new.columns:\n",
    "  df_new[i] = (df_new[i] >= 1).astype(int)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1ajJhhX89HXo"
   },
   "source": [
    "**SVM Models :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "NELUEjH5y8gJ"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "MOfx2gr088E-",
    "outputId": "dfeb623e-0461-4bd9-a091-f665912485a2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.91      0.90      0.90       251\n",
      "           M       0.92      0.93      0.93       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9176672384219554 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_bool = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "6Wv2u3SoR0eR",
    "outputId": "e2877ef0-6d03-487c-c368-c56162ae0b6c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.90      0.90      0.90       251\n",
      "           M       0.92      0.93      0.92       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9142367066895368 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_bool = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "z2TDpZQ9RrmV",
    "outputId": "c28f0297-fe3c-4024-b5f5-a3d7ea00ceb1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.91      0.91      0.91       251\n",
      "           M       0.93      0.93      0.93       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9228130360205832 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_bool = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8U1ekkZOEHLr"
   },
   "source": [
    "**Model Based on TF-IDF values :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ne0QLIX_rKoS"
   },
   "outputs": [],
   "source": [
    "#Calling TfidfVectorizer method from sklearn library to calculate tf-idf values\n",
    "vectorizer = TfidfVectorizer()\n",
    "X = vectorizer.fit_transform(df.Calls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "HW_ZvLb4rSOm",
    "outputId": "c7595983-cc46-4459-ee53-6b97baa48ad7"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_llseek</th>\n",
       "      <th>bind</th>\n",
       "      <th>capget</th>\n",
       "      <th>clock_gettime</th>\n",
       "      <th>clone</th>\n",
       "      <th>close</th>\n",
       "      <th>connect</th>\n",
       "      <th>dup</th>\n",
       "      <th>epoll_create1</th>\n",
       "      <th>epoll_ctl</th>\n",
       "      <th>epoll_pwait</th>\n",
       "      <th>eventfd2</th>\n",
       "      <th>faccessat</th>\n",
       "      <th>fchmod</th>\n",
       "      <th>fchmodat</th>\n",
       "      <th>fcntl</th>\n",
       "      <th>fcntl64</th>\n",
       "      <th>fdatasync</th>\n",
       "      <th>flock</th>\n",
       "      <th>fstat</th>\n",
       "      <th>fstat64</th>\n",
       "      <th>fstatat64</th>\n",
       "      <th>fsync</th>\n",
       "      <th>ftruncate</th>\n",
       "      <th>ftruncate64</th>\n",
       "      <th>futex</th>\n",
       "      <th>getcwd</th>\n",
       "      <th>getdents64</th>\n",
       "      <th>getegid</th>\n",
       "      <th>getegid32</th>\n",
       "      <th>geteuid</th>\n",
       "      <th>geteuid32</th>\n",
       "      <th>getpid</th>\n",
       "      <th>getppid</th>\n",
       "      <th>getpriority</th>\n",
       "      <th>getrlimit</th>\n",
       "      <th>getsockname</th>\n",
       "      <th>getsockopt</th>\n",
       "      <th>gettid</th>\n",
       "      <th>gettimeofday</th>\n",
       "      <th>...</th>\n",
       "      <th>openat</th>\n",
       "      <th>pipe2</th>\n",
       "      <th>ppoll</th>\n",
       "      <th>prctl</th>\n",
       "      <th>pread</th>\n",
       "      <th>pread64</th>\n",
       "      <th>pwrite</th>\n",
       "      <th>pwrite64</th>\n",
       "      <th>read</th>\n",
       "      <th>readlinkat</th>\n",
       "      <th>recvfrom</th>\n",
       "      <th>renameat</th>\n",
       "      <th>rt_sigaction</th>\n",
       "      <th>rt_sigprocmask</th>\n",
       "      <th>rt_sigreturn</th>\n",
       "      <th>sched_getparam</th>\n",
       "      <th>sched_getscheduler</th>\n",
       "      <th>sched_yield</th>\n",
       "      <th>sendmsg</th>\n",
       "      <th>sendto</th>\n",
       "      <th>setpriority</th>\n",
       "      <th>setrlimit</th>\n",
       "      <th>setsockopt</th>\n",
       "      <th>shutdown</th>\n",
       "      <th>sigaction</th>\n",
       "      <th>sigreturn</th>\n",
       "      <th>socket</th>\n",
       "      <th>socketpair</th>\n",
       "      <th>stat64</th>\n",
       "      <th>statfs</th>\n",
       "      <th>statfs64</th>\n",
       "      <th>tgkill</th>\n",
       "      <th>tkill</th>\n",
       "      <th>ugetrlimit</th>\n",
       "      <th>uname</th>\n",
       "      <th>unlinkat</th>\n",
       "      <th>utimensat</th>\n",
       "      <th>wait4</th>\n",
       "      <th>write</th>\n",
       "      <th>writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 102 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    _llseek  ...    writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0.0  ...  0.006720\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0.0  ...  0.021985\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0.0  ...  0.060333\n",
       "com.germany.usedcars.apk.sys_names.txt                  0.0  ...  0.038651\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0.0  ...  0.064521\n",
       "\n",
       "[5 rows x 102 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Performing the same steps as CountVectorizer below\n",
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 244
    },
    "id": "wwnxaMhurtvt",
    "outputId": "a53bd736-7140-4243-8cc6-ff6c240dd66d"
   },
   "outputs": [
    {
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       "      <th>getpid</th>\n",
       "      <th>getppid</th>\n",
       "      <th>getpriority</th>\n",
       "      <th>getrlimit</th>\n",
       "      <th>getsockname</th>\n",
       "      <th>getsockopt</th>\n",
       "      <th>gettid</th>\n",
       "      <th>...</th>\n",
       "      <th>openat</th>\n",
       "      <th>pipe2</th>\n",
       "      <th>ppoll</th>\n",
       "      <th>prctl</th>\n",
       "      <th>pread</th>\n",
       "      <th>pread64</th>\n",
       "      <th>pwrite</th>\n",
       "      <th>pwrite64</th>\n",
       "      <th>read</th>\n",
       "      <th>readlinkat</th>\n",
       "      <th>recvfrom</th>\n",
       "      <th>renameat</th>\n",
       "      <th>rt_sigaction</th>\n",
       "      <th>rt_sigprocmask</th>\n",
       "      <th>rt_sigreturn</th>\n",
       "      <th>sched_getparam</th>\n",
       "      <th>sched_getscheduler</th>\n",
       "      <th>sched_yield</th>\n",
       "      <th>sendmsg</th>\n",
       "      <th>sendto</th>\n",
       "      <th>setpriority</th>\n",
       "      <th>setrlimit</th>\n",
       "      <th>setsockopt</th>\n",
       "      <th>shutdown</th>\n",
       "      <th>sigaction</th>\n",
       "      <th>sigreturn</th>\n",
       "      <th>socket</th>\n",
       "      <th>socketpair</th>\n",
       "      <th>stat64</th>\n",
       "      <th>statfs</th>\n",
       "      <th>statfs64</th>\n",
       "      <th>tgkill</th>\n",
       "      <th>tkill</th>\n",
       "      <th>ugetrlimit</th>\n",
       "      <th>uname</th>\n",
       "      <th>unlinkat</th>\n",
       "      <th>utimensat</th>\n",
       "      <th>wait4</th>\n",
       "      <th>write</th>\n",
       "      <th>writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.986754</td>\n",
       "      <td>0.000108</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.001312</td>\n",
       "      <td>0.055856</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002348</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000673</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001795</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000464</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.025019</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.058736</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000103</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032696</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.030327</td>\n",
       "      <td>0.006720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001487</td>\n",
       "      <td>0.042813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.017802</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.049155</td>\n",
       "      <td>0.434282</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020036</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.024657</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001535</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.019063</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.145516</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.535340</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.095699</td>\n",
       "      <td>0.000702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.422832</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.336049</td>\n",
       "      <td>0.021985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003735</td>\n",
       "      <td>0.009997</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.004545</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.004567</td>\n",
       "      <td>0.728787</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000545</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000308</td>\n",
       "      <td>0.005658</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.007499</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.028450</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000411</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006925</td>\n",
       "      <td>0.00029</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000212</td>\n",
       "      <td>0.008012</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.044794</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>0.259366</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000527</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003551</td>\n",
       "      <td>0.000508</td>\n",
       "      <td>0.159632</td>\n",
       "      <td>0.000596</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000387</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.057219</td>\n",
       "      <td>0.060333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001132</td>\n",
       "      <td>0.010543</td>\n",
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       "      <td>0.005454</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006690</td>\n",
       "      <td>0.510670</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001103</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.005245</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.005328</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.051522</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>0.027054</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.130972</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.395129</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000274</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001978</td>\n",
       "      <td>0.223055</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000178</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.400423</td>\n",
       "      <td>0.038651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003304</td>\n",
       "      <td>0.010766</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003563</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005146</td>\n",
       "      <td>0.622211</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006690</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.009184</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.089079</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006120</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000388</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007106</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.049175</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.323843</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.000215</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.000933</td>\n",
       "      <td>0.271879</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000372</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.091895</td>\n",
       "      <td>0.064521</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 103 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...    writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...  0.006720\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...  0.021985\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...  0.060333\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...  0.038651\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...  0.064521\n",
       "\n",
       "[5 rows x 103 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "u_nIPqFyvJ66"
   },
   "source": [
    "**SVM Models :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "QgM11ogdzA7q"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "s7dOGQLPvVFt",
    "outputId": "ee4b9de5-d429-45c8-83e3-453f84ef4e38"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.94      0.92      0.93       251\n",
      "           M       0.94      0.95      0.95       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9399656946826758 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_tfidf = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "eti3tpPVUQCu",
    "outputId": "bc8f97f0-c35f-4fe0-b0c9-bd38b941881d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.90      0.92      0.91       251\n",
      "           M       0.94      0.92      0.93       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9210977701543739 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_tfidf = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "yEWo4ME_UOia",
    "outputId": "7e539812-5fdb-4e90-c767-4734869401d4"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.95      0.92      0.94       251\n",
      "           M       0.94      0.96      0.95       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9451114922813036 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_tfidf = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 542
    },
    "id": "CFiXia-lH-tv",
    "outputId": "d8c8a63a-72b2-41ec-d238-eed29795b14e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting all the results for comparison\n",
    "kernels = ['rbf','linear','polynomial']\n",
    "feat_rep = ['Occurence of Calls','Boolean','TF-IDF']\n",
    "acc = [acc1_occ, acc2_occ, acc3_occ, acc1_bool, acc2_bool, acc3_bool, acc1_tfidf, acc2_tfidf, acc3_tfidf]\n",
    "acc = [100*i for i in acc]\n",
    "x = []\n",
    "count = 0\n",
    "for i in range(3):\n",
    "  for j in range(3):\n",
    "    x.append([kernels[(j+3)%3], feat_rep[i], acc[count]])\n",
    "    count += 1\n",
    "f = pd.DataFrame(x,columns=['kernels', 'Feature_Representation', 'Accuracy'])\n",
    "f.pivot('kernels','Feature_Representation','Accuracy').plot(kind='bar', figsize =(15,8), yticks=range(0,110,10), ylim=(0,130))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SdNWdZtG_7kk"
   },
   "source": [
    "***We find that on average TF-IDF perform the best among all the feature representation methods on the original dataset while the polynomial kernel has the best performance among kernels.***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "D7_VMqoGoWq7"
   },
   "source": [
    "### **2. Sequence of calls**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0qLEqPidsmOH"
   },
   "source": [
    "**Sequence of 2 calls :**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "h30d2Ozrl2Or"
   },
   "source": [
    "**Model based on Occurence of Calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "IdWP9JXIiYg3"
   },
   "outputs": [],
   "source": [
    "#Calling the CountVectorizer again with bigram parameters for 2 consecutive calls\n",
    "vectorizer = CountVectorizer(ngram_range=(2,2))\n",
    "X = vectorizer.fit_transform(df.Calls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "id": "ZmnTMeTXiyE2",
    "outputId": "2313c1c4-5447-4ca8-e9f7-7a8e4e623b28"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_llseek _llseek</th>\n",
       "      <th>_llseek clock_gettime</th>\n",
       "      <th>_llseek close</th>\n",
       "      <th>_llseek faccessat</th>\n",
       "      <th>_llseek fcntl64</th>\n",
       "      <th>_llseek fstat64</th>\n",
       "      <th>_llseek fstatat64</th>\n",
       "      <th>_llseek ftruncate64</th>\n",
       "      <th>_llseek futex</th>\n",
       "      <th>_llseek madvise</th>\n",
       "      <th>_llseek mmap2</th>\n",
       "      <th>_llseek mprotect</th>\n",
       "      <th>_llseek openat</th>\n",
       "      <th>_llseek read</th>\n",
       "      <th>_llseek write</th>\n",
       "      <th>bind fcntl</th>\n",
       "      <th>bind getsockname</th>\n",
       "      <th>bind ppoll</th>\n",
       "      <th>bind setsockopt</th>\n",
       "      <th>bind socket</th>\n",
       "      <th>capget futex</th>\n",
       "      <th>clock_gettime _llseek</th>\n",
       "      <th>clock_gettime clock_gettime</th>\n",
       "      <th>clock_gettime clone</th>\n",
       "      <th>clock_gettime close</th>\n",
       "      <th>clock_gettime dup</th>\n",
       "      <th>clock_gettime epoll_ctl</th>\n",
       "      <th>clock_gettime epoll_pwait</th>\n",
       "      <th>clock_gettime faccessat</th>\n",
       "      <th>clock_gettime fchmodat</th>\n",
       "      <th>clock_gettime fcntl64</th>\n",
       "      <th>clock_gettime fstat</th>\n",
       "      <th>clock_gettime fstat64</th>\n",
       "      <th>clock_gettime fstatat64</th>\n",
       "      <th>clock_gettime futex</th>\n",
       "      <th>clock_gettime getcwd</th>\n",
       "      <th>clock_gettime getdents64</th>\n",
       "      <th>clock_gettime getppid</th>\n",
       "      <th>clock_gettime getpriority</th>\n",
       "      <th>clock_gettime getrlimit</th>\n",
       "      <th>...</th>\n",
       "      <th>writev getpriority</th>\n",
       "      <th>writev getrlimit</th>\n",
       "      <th>writev getsockname</th>\n",
       "      <th>writev getsockopt</th>\n",
       "      <th>writev gettid</th>\n",
       "      <th>writev gettimeofday</th>\n",
       "      <th>writev getuid</th>\n",
       "      <th>writev getuid32</th>\n",
       "      <th>writev ioctl</th>\n",
       "      <th>writev lseek</th>\n",
       "      <th>writev madvise</th>\n",
       "      <th>writev mkdirat</th>\n",
       "      <th>writev mmap</th>\n",
       "      <th>writev mmap2</th>\n",
       "      <th>writev mprotect</th>\n",
       "      <th>writev munmap</th>\n",
       "      <th>writev newfstatat</th>\n",
       "      <th>writev openat</th>\n",
       "      <th>writev pipe2</th>\n",
       "      <th>writev prctl</th>\n",
       "      <th>writev pread</th>\n",
       "      <th>writev pread64</th>\n",
       "      <th>writev read</th>\n",
       "      <th>writev readlinkat</th>\n",
       "      <th>writev recvfrom</th>\n",
       "      <th>writev renameat</th>\n",
       "      <th>writev rt_sigprocmask</th>\n",
       "      <th>writev rt_sigreturn</th>\n",
       "      <th>writev sched_yield</th>\n",
       "      <th>writev sendmsg</th>\n",
       "      <th>writev sendto</th>\n",
       "      <th>writev setsockopt</th>\n",
       "      <th>writev shutdown</th>\n",
       "      <th>writev socket</th>\n",
       "      <th>writev socketpair</th>\n",
       "      <th>writev statfs</th>\n",
       "      <th>writev statfs64</th>\n",
       "      <th>writev unlinkat</th>\n",
       "      <th>writev write</th>\n",
       "      <th>writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13990</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>47</td>\n",
       "      <td>2260</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2425 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    _llseek _llseek  ...  writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                                 0  ...              1\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                               0  ...             82\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...                0  ...            352\n",
       "com.germany.usedcars.apk.sys_names.txt                            0  ...            280\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt                0  ...            304\n",
       "\n",
       "[5 rows x 2425 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Same process as in Q1. for all the represenations\n",
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "id": "LeL6AQ9qimHm",
    "outputId": "8d32ad69-282e-49bf-a7aa-741052b04368"
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Class</th>\n",
       "      <th>_llseek _llseek</th>\n",
       "      <th>_llseek clock_gettime</th>\n",
       "      <th>_llseek close</th>\n",
       "      <th>_llseek faccessat</th>\n",
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       "      <th>_llseek fstatat64</th>\n",
       "      <th>_llseek ftruncate64</th>\n",
       "      <th>_llseek futex</th>\n",
       "      <th>_llseek madvise</th>\n",
       "      <th>_llseek mmap2</th>\n",
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       "      <th>_llseek openat</th>\n",
       "      <th>_llseek read</th>\n",
       "      <th>_llseek write</th>\n",
       "      <th>bind fcntl</th>\n",
       "      <th>bind getsockname</th>\n",
       "      <th>bind ppoll</th>\n",
       "      <th>bind setsockopt</th>\n",
       "      <th>bind socket</th>\n",
       "      <th>capget futex</th>\n",
       "      <th>clock_gettime _llseek</th>\n",
       "      <th>clock_gettime clock_gettime</th>\n",
       "      <th>clock_gettime clone</th>\n",
       "      <th>clock_gettime close</th>\n",
       "      <th>clock_gettime dup</th>\n",
       "      <th>clock_gettime epoll_ctl</th>\n",
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       "      <th>clock_gettime faccessat</th>\n",
       "      <th>clock_gettime fchmodat</th>\n",
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       "      <th>clock_gettime fstat</th>\n",
       "      <th>clock_gettime fstat64</th>\n",
       "      <th>clock_gettime fstatat64</th>\n",
       "      <th>clock_gettime futex</th>\n",
       "      <th>clock_gettime getcwd</th>\n",
       "      <th>clock_gettime getdents64</th>\n",
       "      <th>clock_gettime getppid</th>\n",
       "      <th>clock_gettime getpriority</th>\n",
       "      <th>...</th>\n",
       "      <th>writev getpriority</th>\n",
       "      <th>writev getrlimit</th>\n",
       "      <th>writev getsockname</th>\n",
       "      <th>writev getsockopt</th>\n",
       "      <th>writev gettid</th>\n",
       "      <th>writev gettimeofday</th>\n",
       "      <th>writev getuid</th>\n",
       "      <th>writev getuid32</th>\n",
       "      <th>writev ioctl</th>\n",
       "      <th>writev lseek</th>\n",
       "      <th>writev madvise</th>\n",
       "      <th>writev mkdirat</th>\n",
       "      <th>writev mmap</th>\n",
       "      <th>writev mmap2</th>\n",
       "      <th>writev mprotect</th>\n",
       "      <th>writev munmap</th>\n",
       "      <th>writev newfstatat</th>\n",
       "      <th>writev openat</th>\n",
       "      <th>writev pipe2</th>\n",
       "      <th>writev prctl</th>\n",
       "      <th>writev pread</th>\n",
       "      <th>writev pread64</th>\n",
       "      <th>writev read</th>\n",
       "      <th>writev readlinkat</th>\n",
       "      <th>writev recvfrom</th>\n",
       "      <th>writev renameat</th>\n",
       "      <th>writev rt_sigprocmask</th>\n",
       "      <th>writev rt_sigreturn</th>\n",
       "      <th>writev sched_yield</th>\n",
       "      <th>writev sendmsg</th>\n",
       "      <th>writev sendto</th>\n",
       "      <th>writev setsockopt</th>\n",
       "      <th>writev shutdown</th>\n",
       "      <th>writev socket</th>\n",
       "      <th>writev socketpair</th>\n",
       "      <th>writev statfs</th>\n",
       "      <th>writev statfs64</th>\n",
       "      <th>writev unlinkat</th>\n",
       "      <th>writev write</th>\n",
       "      <th>writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13990</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>47</td>\n",
       "      <td>2260</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>135</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2426 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...              1\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...             82\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...            352\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...            280\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...            304\n",
       "\n",
       "[5 rows x 2426 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "DT61_0jGjIEh"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "x_norm = normalize(x)\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x_norm, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "JpdCyHD6jskT",
    "outputId": "366b9929-cd7e-47cc-c1f9-173eddd66c75"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.95      0.93      0.94       251\n",
      "           M       0.95      0.96      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9502572898799314 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_occ = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "X0YhI0Rvj_s1",
    "outputId": "377f561b-d8de-4380-f53b-67b06f8a274f"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.93      0.93       251\n",
      "           M       0.95      0.95      0.95       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9399656946826758 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_occ = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "kHF7zQ7fkCyc",
    "outputId": "5c530b83-9ca0-4aa6-bb5b-efe63b96879a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.96      0.93      0.95       251\n",
      "           M       0.95      0.97      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9536878216123499 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_occ = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "m00wG-gqkNu7"
   },
   "source": [
    "**Model Based on Boolean occurence of calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "id": "ILpqPNvKkTYz",
    "outputId": "6dedf9d2-d9cb-44f6-88bc-9a34fe139f70"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Class</th>\n",
       "      <th>_llseek _llseek</th>\n",
       "      <th>_llseek clock_gettime</th>\n",
       "      <th>_llseek close</th>\n",
       "      <th>_llseek faccessat</th>\n",
       "      <th>_llseek fcntl64</th>\n",
       "      <th>_llseek fstat64</th>\n",
       "      <th>_llseek fstatat64</th>\n",
       "      <th>_llseek ftruncate64</th>\n",
       "      <th>_llseek futex</th>\n",
       "      <th>_llseek madvise</th>\n",
       "      <th>_llseek mmap2</th>\n",
       "      <th>_llseek mprotect</th>\n",
       "      <th>_llseek openat</th>\n",
       "      <th>_llseek read</th>\n",
       "      <th>_llseek write</th>\n",
       "      <th>bind fcntl</th>\n",
       "      <th>bind getsockname</th>\n",
       "      <th>bind ppoll</th>\n",
       "      <th>bind setsockopt</th>\n",
       "      <th>bind socket</th>\n",
       "      <th>capget futex</th>\n",
       "      <th>clock_gettime _llseek</th>\n",
       "      <th>clock_gettime clock_gettime</th>\n",
       "      <th>clock_gettime clone</th>\n",
       "      <th>clock_gettime close</th>\n",
       "      <th>clock_gettime dup</th>\n",
       "      <th>clock_gettime epoll_ctl</th>\n",
       "      <th>clock_gettime epoll_pwait</th>\n",
       "      <th>clock_gettime faccessat</th>\n",
       "      <th>clock_gettime fchmodat</th>\n",
       "      <th>clock_gettime fcntl64</th>\n",
       "      <th>clock_gettime fstat</th>\n",
       "      <th>clock_gettime fstat64</th>\n",
       "      <th>clock_gettime fstatat64</th>\n",
       "      <th>clock_gettime futex</th>\n",
       "      <th>clock_gettime getcwd</th>\n",
       "      <th>clock_gettime getdents64</th>\n",
       "      <th>clock_gettime getppid</th>\n",
       "      <th>clock_gettime getpriority</th>\n",
       "      <th>...</th>\n",
       "      <th>writev getpriority</th>\n",
       "      <th>writev getrlimit</th>\n",
       "      <th>writev getsockname</th>\n",
       "      <th>writev getsockopt</th>\n",
       "      <th>writev gettid</th>\n",
       "      <th>writev gettimeofday</th>\n",
       "      <th>writev getuid</th>\n",
       "      <th>writev getuid32</th>\n",
       "      <th>writev ioctl</th>\n",
       "      <th>writev lseek</th>\n",
       "      <th>writev madvise</th>\n",
       "      <th>writev mkdirat</th>\n",
       "      <th>writev mmap</th>\n",
       "      <th>writev mmap2</th>\n",
       "      <th>writev mprotect</th>\n",
       "      <th>writev munmap</th>\n",
       "      <th>writev newfstatat</th>\n",
       "      <th>writev openat</th>\n",
       "      <th>writev pipe2</th>\n",
       "      <th>writev prctl</th>\n",
       "      <th>writev pread</th>\n",
       "      <th>writev pread64</th>\n",
       "      <th>writev read</th>\n",
       "      <th>writev readlinkat</th>\n",
       "      <th>writev recvfrom</th>\n",
       "      <th>writev renameat</th>\n",
       "      <th>writev rt_sigprocmask</th>\n",
       "      <th>writev rt_sigreturn</th>\n",
       "      <th>writev sched_yield</th>\n",
       "      <th>writev sendmsg</th>\n",
       "      <th>writev sendto</th>\n",
       "      <th>writev setsockopt</th>\n",
       "      <th>writev shutdown</th>\n",
       "      <th>writev socket</th>\n",
       "      <th>writev socketpair</th>\n",
       "      <th>writev statfs</th>\n",
       "      <th>writev statfs64</th>\n",
       "      <th>writev unlinkat</th>\n",
       "      <th>writev write</th>\n",
       "      <th>writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2426 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...              1\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...              1\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...              1\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...              1\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...              1\n",
       "\n",
       "[5 rows x 2426 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in df_new.columns:\n",
    "  df_new[i] = (df_new[i] >= 1).astype(int)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "nWd5V8hhn8GP"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "RUO0IbTSn8GS",
    "outputId": "90666bdb-9072-4469-b3d6-11043e0503d0"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.99      0.94      0.97       251\n",
      "           M       0.96      0.99      0.97       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9708404802744426 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_bool = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "qEkRibCNn8GU",
    "outputId": "b4bb4235-5327-4222-90f9-f95b0c22aa81"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.95      0.95      0.95       251\n",
      "           M       0.96      0.96      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9588336192109777 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_bool = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "tbL-1Fbun8GW",
    "outputId": "5a677875-e39f-4e98-df65-3d8f97f1d20d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.99      0.91      0.95       251\n",
      "           M       0.94      0.99      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9588336192109777 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_bool = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ALx19fCejtwF"
   },
   "source": [
    "**Model based on TF-IDF values :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "NPjkOsXag8nj"
   },
   "outputs": [],
   "source": [
    "vectorizer = TfidfVectorizer(ngram_range=(2,2))\n",
    "X = vectorizer.fit_transform(df.Calls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "id": "LtfAJaQug8nl",
    "outputId": "a14fade7-31cd-42d4-8c47-0d0da53bd789"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_llseek _llseek</th>\n",
       "      <th>_llseek clock_gettime</th>\n",
       "      <th>_llseek close</th>\n",
       "      <th>_llseek faccessat</th>\n",
       "      <th>_llseek fcntl64</th>\n",
       "      <th>_llseek fstat64</th>\n",
       "      <th>_llseek fstatat64</th>\n",
       "      <th>_llseek ftruncate64</th>\n",
       "      <th>_llseek futex</th>\n",
       "      <th>_llseek madvise</th>\n",
       "      <th>_llseek mmap2</th>\n",
       "      <th>_llseek mprotect</th>\n",
       "      <th>_llseek openat</th>\n",
       "      <th>_llseek read</th>\n",
       "      <th>_llseek write</th>\n",
       "      <th>bind fcntl</th>\n",
       "      <th>bind getsockname</th>\n",
       "      <th>bind ppoll</th>\n",
       "      <th>bind setsockopt</th>\n",
       "      <th>bind socket</th>\n",
       "      <th>capget futex</th>\n",
       "      <th>clock_gettime _llseek</th>\n",
       "      <th>clock_gettime clock_gettime</th>\n",
       "      <th>clock_gettime clone</th>\n",
       "      <th>clock_gettime close</th>\n",
       "      <th>clock_gettime dup</th>\n",
       "      <th>clock_gettime epoll_ctl</th>\n",
       "      <th>clock_gettime epoll_pwait</th>\n",
       "      <th>clock_gettime faccessat</th>\n",
       "      <th>clock_gettime fchmodat</th>\n",
       "      <th>clock_gettime fcntl64</th>\n",
       "      <th>clock_gettime fstat</th>\n",
       "      <th>clock_gettime fstat64</th>\n",
       "      <th>clock_gettime fstatat64</th>\n",
       "      <th>clock_gettime futex</th>\n",
       "      <th>clock_gettime getcwd</th>\n",
       "      <th>clock_gettime getdents64</th>\n",
       "      <th>clock_gettime getppid</th>\n",
       "      <th>clock_gettime getpriority</th>\n",
       "      <th>clock_gettime getrlimit</th>\n",
       "      <th>...</th>\n",
       "      <th>writev getpriority</th>\n",
       "      <th>writev getrlimit</th>\n",
       "      <th>writev getsockname</th>\n",
       "      <th>writev getsockopt</th>\n",
       "      <th>writev gettid</th>\n",
       "      <th>writev gettimeofday</th>\n",
       "      <th>writev getuid</th>\n",
       "      <th>writev getuid32</th>\n",
       "      <th>writev ioctl</th>\n",
       "      <th>writev lseek</th>\n",
       "      <th>writev madvise</th>\n",
       "      <th>writev mkdirat</th>\n",
       "      <th>writev mmap</th>\n",
       "      <th>writev mmap2</th>\n",
       "      <th>writev mprotect</th>\n",
       "      <th>writev munmap</th>\n",
       "      <th>writev newfstatat</th>\n",
       "      <th>writev openat</th>\n",
       "      <th>writev pipe2</th>\n",
       "      <th>writev prctl</th>\n",
       "      <th>writev pread</th>\n",
       "      <th>writev pread64</th>\n",
       "      <th>writev read</th>\n",
       "      <th>writev readlinkat</th>\n",
       "      <th>writev recvfrom</th>\n",
       "      <th>writev renameat</th>\n",
       "      <th>writev rt_sigprocmask</th>\n",
       "      <th>writev rt_sigreturn</th>\n",
       "      <th>writev sched_yield</th>\n",
       "      <th>writev sendmsg</th>\n",
       "      <th>writev sendto</th>\n",
       "      <th>writev setsockopt</th>\n",
       "      <th>writev shutdown</th>\n",
       "      <th>writev socket</th>\n",
       "      <th>writev socketpair</th>\n",
       "      <th>writev statfs</th>\n",
       "      <th>writev statfs64</th>\n",
       "      <th>writev unlinkat</th>\n",
       "      <th>writev write</th>\n",
       "      <th>writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.8713</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.000284</td>\n",
       "      <td>0.003169</td>\n",
       "      <td>0.145193</td>\n",
       "      <td>0.000072</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000216</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000135</td>\n",
       "      <td>0.004451</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
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       "      <td>0.045344</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2425 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    _llseek _llseek  ...  writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                               0.0  ...       0.000018\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                             0.0  ...       0.022088\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...              0.0  ...       0.041661\n",
       "com.germany.usedcars.apk.sys_names.txt                          0.0  ...       0.032076\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt              0.0  ...       0.045344\n",
       "\n",
       "[5 rows x 2425 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 261
    },
    "id": "i_UsJo_5g8no",
    "outputId": "0d907355-f855-4615-e2d6-10621942b29a"
   },
   "outputs": [
    {
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       "      <th>writev setsockopt</th>\n",
       "      <th>writev shutdown</th>\n",
       "      <th>writev socket</th>\n",
       "      <th>writev socketpair</th>\n",
       "      <th>writev statfs</th>\n",
       "      <th>writev statfs64</th>\n",
       "      <th>writev unlinkat</th>\n",
       "      <th>writev write</th>\n",
       "      <th>writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
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       "      <td>0.008723</td>\n",
       "      <td>0.022088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
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       "      <td>0.003593</td>\n",
       "      <td>0.041661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.002463</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.013005</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002550</td>\n",
       "      <td>0.032076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0.000254</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002136</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>0.000000</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.002084</td>\n",
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       "      <td>0.013252</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.006793</td>\n",
       "      <td>0.045344</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 2426 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...       0.000018\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...       0.022088\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...       0.041661\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...       0.032076\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...       0.045344\n",
       "\n",
       "[5 rows x 2426 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "HJhVgYvZg8nq"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "jxSihzrog8nr",
    "outputId": "f4518961-34f5-4ee3-b194-79e9eb997bd5"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.95      0.93      0.94       251\n",
      "           M       0.95      0.96      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9502572898799314 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_tfidf = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "qY_GtjC4hfkY",
    "outputId": "b6da0244-4c77-48c2-c9a0-668c2824b9d1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.92      0.93      0.93       251\n",
      "           M       0.95      0.94      0.94       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9365351629502573 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_tfidf = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "jzf6gcTth5pZ",
    "outputId": "9c69c338-3f4d-44a3-8bf7-8a0e6b73d76e"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.96      0.93      0.95       251\n",
      "           M       0.95      0.97      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9536878216123499 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_tfidf = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 542
    },
    "id": "SN5MDa43h7xN",
    "outputId": "e71fc4b0-4ca9-4042-cec9-936b317ae0a6"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kernels = ['rbf','linear','polynomial']\n",
    "feat_rep = ['Occurence of Calls','Boolean','TF-IDF']\n",
    "acc = [acc1_occ, acc2_occ, acc3_occ, acc1_bool, acc2_bool, acc3_bool, acc1_tfidf, acc2_tfidf, acc3_tfidf]\n",
    "acc = [100*i for i in acc]\n",
    "x = []\n",
    "count = 0\n",
    "for i in range(3):\n",
    "  for j in range(3):\n",
    "    x.append([kernels[(j+3)%3], feat_rep[i], acc[count]])\n",
    "    count += 1\n",
    "f = pd.DataFrame(x,columns=['kernels', 'Feature_Representation', 'Accuracy'])\n",
    "f.pivot('kernels','Feature_Representation','Accuracy').plot(kind='bar', figsize =(15,8), yticks=range(0,110,10), ylim=(0,130))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IcvRBMWCtBss"
   },
   "source": [
    "**Sequence of 3 calls :**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "H5V6dtV4tBsu"
   },
   "source": [
    "**Model based on Occurence of Calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "JPBpnq6rtBs3"
   },
   "outputs": [],
   "source": [
    "#Calling the CountVectorizer again with trigram parameters for 3 consecutive calls\n",
    "vectorizer = CountVectorizer(ngram_range=(3,3))\n",
    "X = vectorizer.fit_transform(df.Calls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 278
    },
    "id": "Zi37Wx7WtBs7",
    "outputId": "8fa1ac07-08f9-4995-b9a9-48562cf9ad35"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_llseek _llseek _llseek</th>\n",
       "      <th>_llseek _llseek clock_gettime</th>\n",
       "      <th>_llseek _llseek close</th>\n",
       "      <th>_llseek _llseek fcntl64</th>\n",
       "      <th>_llseek _llseek futex</th>\n",
       "      <th>_llseek _llseek madvise</th>\n",
       "      <th>_llseek _llseek mmap2</th>\n",
       "      <th>_llseek _llseek read</th>\n",
       "      <th>_llseek _llseek write</th>\n",
       "      <th>_llseek clock_gettime _llseek</th>\n",
       "      <th>_llseek clock_gettime clock_gettime</th>\n",
       "      <th>_llseek clock_gettime writev</th>\n",
       "      <th>_llseek close fcntl64</th>\n",
       "      <th>_llseek close fstatat64</th>\n",
       "      <th>_llseek close mprotect</th>\n",
       "      <th>_llseek close openat</th>\n",
       "      <th>_llseek close renameat</th>\n",
       "      <th>_llseek close unlinkat</th>\n",
       "      <th>_llseek close write</th>\n",
       "      <th>_llseek faccessat openat</th>\n",
       "      <th>_llseek fcntl64 close</th>\n",
       "      <th>_llseek fcntl64 fcntl64</th>\n",
       "      <th>_llseek fcntl64 munmap</th>\n",
       "      <th>_llseek fcntl64 pread64</th>\n",
       "      <th>_llseek fstat64 fcntl64</th>\n",
       "      <th>_llseek fstat64 fstat64</th>\n",
       "      <th>_llseek fstatat64 fstatat64</th>\n",
       "      <th>_llseek ftruncate64 _llseek</th>\n",
       "      <th>_llseek futex _llseek</th>\n",
       "      <th>_llseek madvise fcntl64</th>\n",
       "      <th>_llseek madvise pread64</th>\n",
       "      <th>_llseek mmap2 clock_gettime</th>\n",
       "      <th>_llseek mmap2 fcntl64</th>\n",
       "      <th>_llseek mmap2 madvise</th>\n",
       "      <th>_llseek mmap2 munmap</th>\n",
       "      <th>_llseek mmap2 openat</th>\n",
       "      <th>_llseek mmap2 pread64</th>\n",
       "      <th>_llseek mprotect mprotect</th>\n",
       "      <th>_llseek openat read</th>\n",
       "      <th>_llseek read _llseek</th>\n",
       "      <th>...</th>\n",
       "      <th>writev writev fcntl</th>\n",
       "      <th>writev writev flock</th>\n",
       "      <th>writev writev fstat</th>\n",
       "      <th>writev writev futex</th>\n",
       "      <th>writev writev getdents64</th>\n",
       "      <th>writev writev getpriority</th>\n",
       "      <th>writev writev getrlimit</th>\n",
       "      <th>writev writev getsockname</th>\n",
       "      <th>writev writev gettid</th>\n",
       "      <th>writev writev gettimeofday</th>\n",
       "      <th>writev writev getuid</th>\n",
       "      <th>writev writev getuid32</th>\n",
       "      <th>writev writev ioctl</th>\n",
       "      <th>writev writev lseek</th>\n",
       "      <th>writev writev madvise</th>\n",
       "      <th>writev writev mkdirat</th>\n",
       "      <th>writev writev mmap</th>\n",
       "      <th>writev writev mmap2</th>\n",
       "      <th>writev writev mprotect</th>\n",
       "      <th>writev writev munmap</th>\n",
       "      <th>writev writev newfstatat</th>\n",
       "      <th>writev writev openat</th>\n",
       "      <th>writev writev pipe2</th>\n",
       "      <th>writev writev prctl</th>\n",
       "      <th>writev writev pread</th>\n",
       "      <th>writev writev pread64</th>\n",
       "      <th>writev writev read</th>\n",
       "      <th>writev writev recvfrom</th>\n",
       "      <th>writev writev renameat</th>\n",
       "      <th>writev writev rt_sigprocmask</th>\n",
       "      <th>writev writev rt_sigreturn</th>\n",
       "      <th>writev writev sched_yield</th>\n",
       "      <th>writev writev sendmsg</th>\n",
       "      <th>writev writev sendto</th>\n",
       "      <th>writev writev setsockopt</th>\n",
       "      <th>writev writev socket</th>\n",
       "      <th>writev writev socketpair</th>\n",
       "      <th>writev writev statfs</th>\n",
       "      <th>writev writev write</th>\n",
       "      <th>writev writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23331 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    _llseek _llseek _llseek  ...  writev writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                                         0  ...                     0\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                                       0  ...                    68\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...                        0  ...                   256\n",
       "com.germany.usedcars.apk.sys_names.txt                                    0  ...                   190\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt                        0  ...                   226\n",
       "\n",
       "[5 rows x 23331 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 278
    },
    "id": "GKQDcf1itBs8",
    "outputId": "10d8b87c-c39d-4451-e9d2-660a6b760c0f"
   },
   "outputs": [
    {
     "data": {
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       "      <th>Class</th>\n",
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       "      <th>_llseek fstat64 fstat64</th>\n",
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       "      <th>writev writev newfstatat</th>\n",
       "      <th>writev writev openat</th>\n",
       "      <th>writev writev pipe2</th>\n",
       "      <th>writev writev prctl</th>\n",
       "      <th>writev writev pread</th>\n",
       "      <th>writev writev pread64</th>\n",
       "      <th>writev writev read</th>\n",
       "      <th>writev writev recvfrom</th>\n",
       "      <th>writev writev renameat</th>\n",
       "      <th>writev writev rt_sigprocmask</th>\n",
       "      <th>writev writev rt_sigreturn</th>\n",
       "      <th>writev writev sched_yield</th>\n",
       "      <th>writev writev sendmsg</th>\n",
       "      <th>writev writev sendto</th>\n",
       "      <th>writev writev setsockopt</th>\n",
       "      <th>writev writev socket</th>\n",
       "      <th>writev writev socketpair</th>\n",
       "      <th>writev writev statfs</th>\n",
       "      <th>writev writev write</th>\n",
       "      <th>writev writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>226</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23332 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...                     0\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...                    68\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...                   256\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...                   190\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...                   226\n",
       "\n",
       "[5 rows x 23332 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "IK0RJfy3tBs-"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "x = normalize(x)\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "SavZpSM1tBtB",
    "outputId": "b4d438d9-f991-48f0-c1fb-feab9db448d7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.96      0.94      0.95       251\n",
      "           M       0.95      0.97      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9536878216123499 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_occ = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "xy51sic0tBtD",
    "outputId": "03e386f0-1091-43e6-f00d-8f4c6a03f206"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.93      0.93       251\n",
      "           M       0.95      0.95      0.95       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9416809605488851 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_occ = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "2lnwWnuztBtE",
    "outputId": "6f8f89dc-c72b-4d5a-fe9e-9599d5290841"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.96      0.94      0.95       251\n",
      "           M       0.95      0.97      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9536878216123499 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_occ = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "q2dp96AbtBtG"
   },
   "source": [
    "**Model Based on Boolean occurence of calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 278
    },
    "id": "6KnPRIZbtBtG",
    "outputId": "66b9841c-2a98-4739-99e7-21704ce2fa78"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Class</th>\n",
       "      <th>_llseek _llseek _llseek</th>\n",
       "      <th>_llseek _llseek clock_gettime</th>\n",
       "      <th>_llseek _llseek close</th>\n",
       "      <th>_llseek _llseek fcntl64</th>\n",
       "      <th>_llseek _llseek futex</th>\n",
       "      <th>_llseek _llseek madvise</th>\n",
       "      <th>_llseek _llseek mmap2</th>\n",
       "      <th>_llseek _llseek read</th>\n",
       "      <th>_llseek _llseek write</th>\n",
       "      <th>_llseek clock_gettime _llseek</th>\n",
       "      <th>_llseek clock_gettime clock_gettime</th>\n",
       "      <th>_llseek clock_gettime writev</th>\n",
       "      <th>_llseek close fcntl64</th>\n",
       "      <th>_llseek close fstatat64</th>\n",
       "      <th>_llseek close mprotect</th>\n",
       "      <th>_llseek close openat</th>\n",
       "      <th>_llseek close renameat</th>\n",
       "      <th>_llseek close unlinkat</th>\n",
       "      <th>_llseek close write</th>\n",
       "      <th>_llseek faccessat openat</th>\n",
       "      <th>_llseek fcntl64 close</th>\n",
       "      <th>_llseek fcntl64 fcntl64</th>\n",
       "      <th>_llseek fcntl64 munmap</th>\n",
       "      <th>_llseek fcntl64 pread64</th>\n",
       "      <th>_llseek fstat64 fcntl64</th>\n",
       "      <th>_llseek fstat64 fstat64</th>\n",
       "      <th>_llseek fstatat64 fstatat64</th>\n",
       "      <th>_llseek ftruncate64 _llseek</th>\n",
       "      <th>_llseek futex _llseek</th>\n",
       "      <th>_llseek madvise fcntl64</th>\n",
       "      <th>_llseek madvise pread64</th>\n",
       "      <th>_llseek mmap2 clock_gettime</th>\n",
       "      <th>_llseek mmap2 fcntl64</th>\n",
       "      <th>_llseek mmap2 madvise</th>\n",
       "      <th>_llseek mmap2 munmap</th>\n",
       "      <th>_llseek mmap2 openat</th>\n",
       "      <th>_llseek mmap2 pread64</th>\n",
       "      <th>_llseek mprotect mprotect</th>\n",
       "      <th>_llseek openat read</th>\n",
       "      <th>...</th>\n",
       "      <th>writev writev fcntl</th>\n",
       "      <th>writev writev flock</th>\n",
       "      <th>writev writev fstat</th>\n",
       "      <th>writev writev futex</th>\n",
       "      <th>writev writev getdents64</th>\n",
       "      <th>writev writev getpriority</th>\n",
       "      <th>writev writev getrlimit</th>\n",
       "      <th>writev writev getsockname</th>\n",
       "      <th>writev writev gettid</th>\n",
       "      <th>writev writev gettimeofday</th>\n",
       "      <th>writev writev getuid</th>\n",
       "      <th>writev writev getuid32</th>\n",
       "      <th>writev writev ioctl</th>\n",
       "      <th>writev writev lseek</th>\n",
       "      <th>writev writev madvise</th>\n",
       "      <th>writev writev mkdirat</th>\n",
       "      <th>writev writev mmap</th>\n",
       "      <th>writev writev mmap2</th>\n",
       "      <th>writev writev mprotect</th>\n",
       "      <th>writev writev munmap</th>\n",
       "      <th>writev writev newfstatat</th>\n",
       "      <th>writev writev openat</th>\n",
       "      <th>writev writev pipe2</th>\n",
       "      <th>writev writev prctl</th>\n",
       "      <th>writev writev pread</th>\n",
       "      <th>writev writev pread64</th>\n",
       "      <th>writev writev read</th>\n",
       "      <th>writev writev recvfrom</th>\n",
       "      <th>writev writev renameat</th>\n",
       "      <th>writev writev rt_sigprocmask</th>\n",
       "      <th>writev writev rt_sigreturn</th>\n",
       "      <th>writev writev sched_yield</th>\n",
       "      <th>writev writev sendmsg</th>\n",
       "      <th>writev writev sendto</th>\n",
       "      <th>writev writev setsockopt</th>\n",
       "      <th>writev writev socket</th>\n",
       "      <th>writev writev socketpair</th>\n",
       "      <th>writev writev statfs</th>\n",
       "      <th>writev writev write</th>\n",
       "      <th>writev writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.bitdrome.rmc2.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23332 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...                     0\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...                     1\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...                     1\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...                     1\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...                     1\n",
       "\n",
       "[5 rows x 23332 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in df_new.columns:\n",
    "  df_new[i] = (df_new[i] >= 1).astype(int)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "eUoNYDvrtBtI"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "viAPOIzItBtK",
    "outputId": "85954bf2-f18a-4e40-b6a9-68a4f41a901a"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.99      0.94      0.97       251\n",
      "           M       0.96      0.99      0.98       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9725557461406518 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_bool = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "0RktyVuUtBtM",
    "outputId": "3c383349-8503-45c6-f26f-904c62d3ee53"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mVlpZJoIngQpJAyXtCowH5tbsjIi3IqJnRAyIiAHAImBMRCzJMCYzM6sjs0QQER8AFwLzgdXAXRGxUtLVksZkdV0zM2ueJt8sliTg74ADIuLqdL7iT0TEE00dGxHzqDMcRURc3kDZkUVFbGZmO1UxLYKbgaOBCen62yTvB5iZWTtQzKBzIyLiCElPAUTE1vSev5mZtQPFtAjeT98SDqidj+CjTKMyM7OSKSYR/AT4NbCvpOuA3wPfzzQqMzMrmWKGoZ4paSkwimR4idMiYnXmkZmZWUkU89RQf+Ad4DeF2yLilSwDMzOz0iims/h+kv4BAZ2BgcBzwKEZxmVmZiVSzK2hwwrX04HiLsgsIjMzK6lmv1mcDj89osmCZmbWJhTTRzC5YHUX4AhgY2YRmZlZSRXTR9C1YPkDkj6DX2UTjpmZlVqjiSB9kaxrRPxjieIxM7MSa7CPQFLHiPgQOKaE8ZiZWYk11iJ4gqQ/YLmkucDdwJ9qdkbEf2Ucm5mZlUAxfQSdgc0kcxTXvE8QgBOBmVk70Fgi2Dd9YuhZ/pIAanjeYDOzdqKxRNAB6MLHE0ANJwIzs3aisURQHRFXlywSMzMri8beLK6vJWBmZu1MY4lgVMmiMDOzsmkwEUTEllIGYmZm5dHsQefMzKx9cSIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5zLNBFIGi3pOUlrJU2pZ/9kSaskrZD0P5L2zzIeMzPbUWaJIJ3v+CbgJGAwMEHS4DrFngIqI2IocA/wr1nFY2Zm9cuyRXAksDYiXoyI94DZwNjCAhGxICLeSVcXAX0zjMfMzOqRZSLoA6wvWK9KtzXkHOCB+nZImiRpiaQlmzZt2okhmpnZX0VnsaSvAJXADfXtj4hpEVEZEZW9evUqbXBmZu1cMZPXt9QGoF/Bet9028dI+hxwGfCZiPjfDOMxM7N6ZNkieBKokDRQ0q7AeGBuYQFJhwM/A8ZExOsZxmJmZg3ILBFExAfAhcB8YDVwV0SslHS1pDFpsRuALsDdkpZLmtvA6czMLCNZ3hoiIuYB8+psu7xg+XNZXt/MzJr2V9FZbGZm5eNEYGaWc04EZmY550RgZpZzTgRmZjnnRGBmlnNOBGZmOedEYGaWc04EZmY550RgZpZzTgRmZjnnRGBmlnNOBGZmOedEYGaWc04EZmY550RgZpZzTgRmZjnnRGBmlnNOBGZmOedEYGaWc04EZmY517HcAZhZtt5//32qqqp49913yx2KlUDnzp3p27cvnTp1KvoYJwKzdq6qqoquXbsyYMAAJJU7HMtQRLB582aqqqoYOHBg0cf51pBZO/fuu+/So0cPJ4EckESPHj2a3fpzIjDLASeB/GjJz9qJwMws55wIzCxz1113HYceeihDhw5l2LBhLF68mKuuuorvfOc7Hyu3fPlyDjnkEAC2b9/Oeeedx4EHHsjw4cMZOXIkixcv3uHcEcFnP/tZtm3bVrvt3nvvRRJ//OMfa7ctXLiQU0899WPHTpw4kXvuuQdIOtWnTJlCRUUFRxxxBEcffTQPPPBAq+q9efNmjj/+eLp06cKFF17YYLktW7ZwwgknUFFRwQknnMDWrVtr6/atb32LQYMGMXToUJYtWwbApk2bGD16dKtiK+REYGaZevzxx7nvvvtYtmwZK1as4KGHHqJfv35MmDCBO++882NlZ8+ezYQJEwD4+te/zj777MOaNWtYunQpv/jFL3jjjTd2OP+8efP41Kc+Rbdu3Wq3zZo1i2OPPZZZs2YVHef3vvc9qqurefbZZ1m2bBn33nsvb7/9dgtrnejcuTPXXHMNP/jBDxotN3XqVEaNGsWaNWsYNWoUU6dOBeCBBx5gzZo1rFmzhmnTpnH++ecD0KtXL3r37s1jjz3Wqvhq+Kkhsxy56jcrWbVxW9MFm2HwJ7txxRcObXB/dXU1PXv2ZLfddgOgZ8+etfv23ntvFi9ezIgRIwC46667mD9/Pi+88AKLFy9m5syZ7LJL8n114MCB9T4JM3PmTCZNmlS7vn37dn7/+9+zYMECvvCFL3DVVVc1WYd33nmHW265hZdeeqk2zv32248zzzyziL+Bhu25554ce+yxrF27ttFyc+bMYeHChQCcffbZjBw5kuuvv545c+Zw1llnIYmjjjqKN998k+rqanr37s1pp53GzJkzOeaYY1oVI7hFYGYZO/HEE1m/fj0HHXQQF1xwAQ8//HDtvgkTJjB79mwAFi1axD777ENFRQUrV65k2LBhdOjQocnzP/bYYwwfPrx2fc6cOYwePZqDDjqIHj16sHTp0ibPsXbtWvr37/+xVkVDLrnkEoYNG7bDp+ZbfEu89tpr9O7dG4BPfOITvPbaawBs2LCBfv361Zbr27cvGzZsAKCyspJHH320xdcs5BaBWY409s09K126dGHp0qU8+uijLFiwgHHjxjF16lQmTpzIuHHj+PSnP80Pf/jDj90Wao4tW7bQtWvX2vVZs2Zx8cUXAzB+/HhmzZrF8OHDG3yaprlP2dx4443NjrE5JBUV07777svGjRt3yjUzTQSSRgM/BjoAt0bE1Dr7dwNuB4YDm4FxEbEuy5jMrPQ6dOjAyJEjGTlyJIcddhgzZsxg4sSJ9OvXj4EDB/Lwww/zq1/9iscffxyAQw89lKeffpoPP/ywyVZBx44d+eijj9hll13YsmULv/vd73jmmWeQxIcffogkbrjhBnr06FHbCVtjy5Yt9OzZk0GDBvHKK6+wbdu2JlsFl1xyCQsWLNhh+/jx45kyZUoz/2YS++23X+0tn+rqavbdd18A+vTpw/r162vLVVVV0adPHyB5P2T33Xdv0fXqyuzWkKQOwE3AScBgYIKkwXWKnQNsjYhBwI3A9VnFY2bl8dxzz7FmzZra9eXLl7P//vvXrk+YMIFLLrmEAw44gL59+wJw4IEHUllZyRVXXEFEALBu3Truv//+Hc5/8MEH8+KLLwJwzz338NWvfpWXX36ZdevWsX79egYOHMijjz5KRUUFGzduZPXq1QC8/PLLPP300wwbNow99tiDc845h4svvpj33nsPSJ7Mufvuu3e43o033sjy5ct3+LQ0CQCMGTOGGTNmADBjxgzGjh1bu/32228nIli0aBHdu3evvYX0/PPPM2TIkBZfs1CWfQRHAmsj4sWIeA+YDYytU2YsMCNdvgcYJb/5YtaubN++nbPPPpvBgwczdOhQVq1axZVXXlm7/0tf+hIrV67c4bbQrbfeymuvvcagQYMYMmQIEydOrP2mXOiUU06p7WidNWsWX/ziFz+2//TTT2fWrFnstttu/PKXv+RrX/saw4YN44wzzuDWW2+le/fuAFx77bX06tWLwYMHM2TIEE499dSi+gyaMmDAACZPnsz06dPp27cvq1atApKnopYsWQLAlClTePDBB6moqOChhx6qTSonn3wyBxxwAIMGDeLcc8/l5ptvrj3vggULOOWUU1odH4Bqsu3OJukMYHREfD1d/yowIiIuLCjzbFqmKl1/IS3zRp1zTQImAfTv33/4yy+/3Ox4rvrNSqA890jNymn16tW1z+a3R9XV1Zx11lk8+OCD5Q6lpI477jjmzJnD3nvvvcO++n7mkpZGRGV952oTncURMQ2YBlBZWdmizOUEYNY+9e7dm3PPPbeo+/vtxaZNm5g8eXK9SaAlskwEG4B+Bet90231lamS1BHoTtJpbGZWtNY+79/W9OrVi9NOO22nnS/LPoIngQpJAyXtCowH5tYpMxc4O10+A/hdZHWvyizH/N8qP1rys84sEUTEB8CFwHxgNXBXRKyUdLWkMWmxnwM9JK0FJgMt73Y3s3p17tyZzZs3OxnkQM18BJ07d27WcZl1FmelsrIyanrazaxpnqEsXxqaoazNdxabWct16tSpWbNVWf54rCEzs5xzIjAzyzknAjOznGtzncWSNgHNf7U40RPYcWaL9s11zgfXOR9aU+f9I6JXfTvaXCJoDUlLGuo1b69c53xwnfMhqzr71pCZWc45EZiZ5VzeEsG0cgdQBq5zPrjO+ZBJnXPVR2BmZjvKW4vAzMzqcCIwM8u5dpkIJI2W9JyktZJ2GNFU0m6S7kz3L5Y0oPRR7lxF1HmypFWSVkj6H0n713eetqSpOheUO11SSGrzjxoWU2dJZ6Y/65WS7ih1jDtbEf+2+0taIOmp9N/3yeWIc2eRdJuk19MZHOvbL0k/Sf8+Vkg6otUXjYh29QE6AC8ABwC7Ak8Dg+uUuQD4abo8Hriz3HGXoM7HA3uky+fnoc5pua7AI8AioLLccZfg51wBPAXsna7vW+64S1DnacD56fJgYF25425lnY8DjgCebWD/ycADgICjgMWtvWZ7bBEcCayNiBcj4j1gNjC2TpmxwIx0+R5glCSVMMadrck6R8SCiHgnXV1EMmNcW1bMzxngGuB6oD2MwVxMnc8FboqIrQAR8XqJY9zZiqlzADVzVHYHNpYwvp0uIh4BtjRSZCxweyQWAXtJ6t2aa7bHRNAHWF+wXpVuq7dMJBPovAX0KEl02SimzoXOIflG0ZY1Wee0ydwvIu4vZWAZKubnfBBwkKTHJC2SNLpk0WWjmDpfCXxFUhUwD7ioNKGVTXP/vzfJ8xHkjKSvAJXAZ8odS5Yk7QL8CJhY5lBKrSPJ7aGRJK2+RyQdFhFvljWqbE0ApkfEDyUdDfynpCER8VG5A2sr2mOLYAPQr2C9b7qt3jKSOpI0JzeXJLpsFFNnJH0OuAwYExH/W6LYstJUnbsCQ4CFktaR3Eud28Y7jIv5OVcBcyPi/Yh4CXieJDG0VcXU+RzgLoCIeBzoTDI4W3tV1P/35miPieBJoELSQEm7knQGz61TZi5wdrp8BvC7SHth2qgm6yzpcOBnJEmgrd83hibqHBFvRUTPiBgQEQNI+kXGRERbnue0mH/b95K0BpDUk+RW0YulDHInK6bOrwCjACQdQpIINpU0ytKaC5yVPj10FPBWRFS35oTt7tZQRHwg6UJgPskTB7dFxEpJVwNLImIu8HOS5uNakk6Z8eWLuPWKrPMNQBfg7rRf/JWIGFO2oFupyDq3K0XWeT5woqRVwIfAtyOizbZ2i6zzpcAtki4h6Tie2Ja/2EmaRZLMe6b9HlcAnQAi4qck/SAnA2uBd4Cvtfqabfjvy8zMdoL2eGvIzMyawYnAzCznnAjMzHLOicDMLOecCMzMcs6JwP4qSfpQ0vKCz4BGym7fCdebLuml9FrL0jdUm3uOWyUNTpf/uc6+P7Q2xvQ8NX8vz0r6jaS9mig/rK2PxmnZ8+Oj9ldJ0vaI6LKzyzZyjunAfRFxj6QTgR9ExNBWnK/VMTV1XkkzgOcj4rpGyk8kGXX1wp0di7UfbhFYmyCpSzqPwjJJz0jaYaRRSb0lPVLwjflv0+0nSno8PfZuSU39gn4EGJQeOzk917OS/iHdtqek+yU9nW4fl25fKKlS0lRg9zSOmem+7emfsyWdUhDzdElnSOog6QZJT6ZjzJ9XxF/L46SDjUk6Mq3jU5L+IOng9E3cq4FxaSzj0thvk/REWra+EVstb8o99rY//tT3IXkrdnn6+TXJW/Dd0n09Sd6qrGnRbk//vBS4LF3uQDLeUE+SX+x7ptv/Cbi8nutNB85Il78ELAaGA88Ae5K8lb0SOBw4Hbil4Nju6Z8LSec8qImpoExNjF8EZqTLu5KMIrk7MAn4brp9N2AJMLCeOLcX1O9uYHS63g3omC5/DvhVujwR+PeC478PfCVd3otkLKI9y/3z9qe8n3Y3xIS1G3+OiGE1K5I6Ad+XdBzwEck34f2AVwuOeRK4LS17b0Qsl/QZkslKHkuH1tiV5Jt0fW6Q9F2ScWrOIRm/5tcR8ac0hv8C/hb4LfBDSdeT3E56tBn1egD4saTdgNHAIxHx5/R21FBJZ6TlupMMFvdSneN3l7Q8rf9q4MGC8jMkVZAMs9CpgeufCIyR9I/pemegf3ouyyknAmsr/g7oBQyPiPeVjCjaubBARDySJopTgOmSfgRsBR6MiAlFXOPbEXFPzYqkUfUViojnlcx1cDJwraT/iYiri6lERLwraSHweWAcyUQrkMw2dVFEzIqOgCsAAAFdSURBVG/iFH+OiGGS9iAZf+ebwE9IJuBZEBFfTDvWFzZwvIDTI+K5YuK1fHAfgbUV3YHX0yRwPLDDnMtK5mF+LSJuAW4lme5vEXCMpJp7/ntKOqjIaz4KnCZpD0l7ktzWeVTSJ4F3IuKXJIP51Tdn7Ptpy6Q+d5IMFFbTuoDkl/r5NcdIOii9Zr0imW3uW8Cl+stQ6jVDEU8sKPo2yS2yGvOBi5Q2j5SMSms550RgbcVMoFLSM8BZwB/rKTMSeFrSUyTftn8cEZtIfjHOkrSC5LbQ3xRzwYhYRtJ38ARJn8GtEfEUcBjwRHqL5grg2noOnwasqOksruO/SSYGeiiS6RchSVyrgGVKJi3/GU202NNYVpBMzPKvwL+kdS88bgEwuKazmKTl0CmNbWW6bjnnx0fNzHLOLQIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5z7/09mnSevgPqmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.98      0.96      0.97       251\n",
      "           M       0.97      0.99      0.98       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9759862778730704 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_bool = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "5ttwlk2BtBtO",
    "outputId": "00feb108-e8dc-45fc-8cf2-f4f90653374f"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       1.00      0.89      0.94       251\n",
      "           M       0.92      1.00      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9519725557461407 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_bool = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kEDdSxVEtBtQ"
   },
   "source": [
    "**Model based on TF-IDF values :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "ybOKxSzTtBtW"
   },
   "outputs": [],
   "source": [
    "vectorizer = TfidfVectorizer(ngram_range=(3,3))\n",
    "X = vectorizer.fit_transform(df.Calls)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 278
    },
    "id": "BdLhcnLmtBtX",
    "outputId": "d19d8c42-9996-495e-840b-50298aca0cc0"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>_llseek _llseek _llseek</th>\n",
       "      <th>_llseek _llseek clock_gettime</th>\n",
       "      <th>_llseek _llseek close</th>\n",
       "      <th>_llseek _llseek fcntl64</th>\n",
       "      <th>_llseek _llseek futex</th>\n",
       "      <th>_llseek _llseek madvise</th>\n",
       "      <th>_llseek _llseek mmap2</th>\n",
       "      <th>_llseek _llseek read</th>\n",
       "      <th>_llseek _llseek write</th>\n",
       "      <th>_llseek clock_gettime _llseek</th>\n",
       "      <th>_llseek clock_gettime clock_gettime</th>\n",
       "      <th>_llseek clock_gettime writev</th>\n",
       "      <th>_llseek close fcntl64</th>\n",
       "      <th>_llseek close fstatat64</th>\n",
       "      <th>_llseek close mprotect</th>\n",
       "      <th>_llseek close openat</th>\n",
       "      <th>_llseek close renameat</th>\n",
       "      <th>_llseek close unlinkat</th>\n",
       "      <th>_llseek close write</th>\n",
       "      <th>_llseek faccessat openat</th>\n",
       "      <th>_llseek fcntl64 close</th>\n",
       "      <th>_llseek fcntl64 fcntl64</th>\n",
       "      <th>_llseek fcntl64 munmap</th>\n",
       "      <th>_llseek fcntl64 pread64</th>\n",
       "      <th>_llseek fstat64 fcntl64</th>\n",
       "      <th>_llseek fstat64 fstat64</th>\n",
       "      <th>_llseek fstatat64 fstatat64</th>\n",
       "      <th>_llseek ftruncate64 _llseek</th>\n",
       "      <th>_llseek futex _llseek</th>\n",
       "      <th>_llseek madvise fcntl64</th>\n",
       "      <th>_llseek madvise pread64</th>\n",
       "      <th>_llseek mmap2 clock_gettime</th>\n",
       "      <th>_llseek mmap2 fcntl64</th>\n",
       "      <th>_llseek mmap2 madvise</th>\n",
       "      <th>_llseek mmap2 munmap</th>\n",
       "      <th>_llseek mmap2 openat</th>\n",
       "      <th>_llseek mmap2 pread64</th>\n",
       "      <th>_llseek mprotect mprotect</th>\n",
       "      <th>_llseek openat read</th>\n",
       "      <th>_llseek read _llseek</th>\n",
       "      <th>...</th>\n",
       "      <th>writev writev fcntl</th>\n",
       "      <th>writev writev flock</th>\n",
       "      <th>writev writev fstat</th>\n",
       "      <th>writev writev futex</th>\n",
       "      <th>writev writev getdents64</th>\n",
       "      <th>writev writev getpriority</th>\n",
       "      <th>writev writev getrlimit</th>\n",
       "      <th>writev writev getsockname</th>\n",
       "      <th>writev writev gettid</th>\n",
       "      <th>writev writev gettimeofday</th>\n",
       "      <th>writev writev getuid</th>\n",
       "      <th>writev writev getuid32</th>\n",
       "      <th>writev writev ioctl</th>\n",
       "      <th>writev writev lseek</th>\n",
       "      <th>writev writev madvise</th>\n",
       "      <th>writev writev mkdirat</th>\n",
       "      <th>writev writev mmap</th>\n",
       "      <th>writev writev mmap2</th>\n",
       "      <th>writev writev mprotect</th>\n",
       "      <th>writev writev munmap</th>\n",
       "      <th>writev writev newfstatat</th>\n",
       "      <th>writev writev openat</th>\n",
       "      <th>writev writev pipe2</th>\n",
       "      <th>writev writev prctl</th>\n",
       "      <th>writev writev pread</th>\n",
       "      <th>writev writev pread64</th>\n",
       "      <th>writev writev read</th>\n",
       "      <th>writev writev recvfrom</th>\n",
       "      <th>writev writev renameat</th>\n",
       "      <th>writev writev rt_sigprocmask</th>\n",
       "      <th>writev writev rt_sigreturn</th>\n",
       "      <th>writev writev sched_yield</th>\n",
       "      <th>writev writev sendmsg</th>\n",
       "      <th>writev writev sendto</th>\n",
       "      <th>writev writev setsockopt</th>\n",
       "      <th>writev writev socket</th>\n",
       "      <th>writev writev socketpair</th>\n",
       "      <th>writev writev statfs</th>\n",
       "      <th>writev writev write</th>\n",
       "      <th>writev writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23331 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    _llseek _llseek _llseek  ...  writev writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                                       0.0  ...              0.000000\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                                     0.0  ...              0.027548\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...                      0.0  ...              0.037926\n",
       "com.germany.usedcars.apk.sys_names.txt                                  0.0  ...              0.032364\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt                      0.0  ...              0.044748\n",
       "\n",
       "[5 rows x 23331 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 278
    },
    "id": "J0MRzZoTtBtc",
    "outputId": "be70bb73-f240-4bcc-eaab-63078c1e30d3"
   },
   "outputs": [
    {
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       "      <th>writev writev rt_sigreturn</th>\n",
       "      <th>writev writev sched_yield</th>\n",
       "      <th>writev writev sendmsg</th>\n",
       "      <th>writev writev sendto</th>\n",
       "      <th>writev writev setsockopt</th>\n",
       "      <th>writev writev socket</th>\n",
       "      <th>writev writev socketpair</th>\n",
       "      <th>writev writev statfs</th>\n",
       "      <th>writev writev write</th>\n",
       "      <th>writev writev writev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>com.foodiestrip.apk.sys_names.txt</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <td>0.027548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.appbuilder.legitimateonlinejobs.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
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       "      <td>0.037926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.germany.usedcars.apk.sys_names.txt</th>\n",
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       "      <td>0.003817</td>\n",
       "      <td>0.032364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt</th>\n",
       "      <td>0</td>\n",
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       "      <td>0.044748</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23332 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Class  ...  writev writev writev\n",
       "com.foodiestrip.apk.sys_names.txt                       0  ...              0.000000\n",
       "com.bitdrome.rmc2.apk.sys_names.txt                     0  ...              0.027548\n",
       "com.appbuilder.legitimateonlinejobs.apk.sys_nam...      0  ...              0.037926\n",
       "com.germany.usedcars.apk.sys_names.txt                  0  ...              0.032364\n",
       "com.BATUTAAPPS.funnyfaketvprankk.apk.sys_names.txt      0  ...              0.044748\n",
       "\n",
       "[5 rows x 23332 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "df_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "l8ScdSb8tBtd"
   },
   "outputs": [],
   "source": [
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']\n",
    "train_x, test_x, train_y, test_y = train_test_split(x, y, test_size = 0.1, random_state = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "Zvhwo8rgtBtf",
    "outputId": "03f65279-a3c8-4732-cf63-724f043a5d46"
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.96      0.93      0.95       251\n",
      "           M       0.95      0.97      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9554030874785592 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc1_tfidf = model('rbf', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "2AYj3Dr6tBth",
    "outputId": "638751ae-6ee2-4de3-d9d8-cd63746da30b"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.93      0.94      0.93       251\n",
      "           M       0.95      0.95      0.95       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9433962264150944 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc2_tfidf = model('linear', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 446
    },
    "id": "6GgASlJltBtj",
    "outputId": "a6f685eb-c9d0-48d5-ab59-21e67b282a81"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           B       0.95      0.93      0.94       251\n",
      "           M       0.95      0.96      0.96       332\n",
      "\n",
      "     \n",
      " Accuracy : 0.9502572898799314 \n",
      "\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "acc3_tfidf = model('poly', train_x, train_y, test_x, test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 542
    },
    "id": "J4SHcMnxtBtk",
    "outputId": "4864494b-b5d0-4e1f-865f-694eee6fd148"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kernels = ['rbf','linear','polynomial']\n",
    "feat_rep = ['Occurence of Calls','Boolean','TF-IDF']\n",
    "acc = [acc1_occ, acc2_occ, acc3_occ, acc1_bool, acc2_bool, acc3_bool, acc1_tfidf, acc2_tfidf, acc3_tfidf]\n",
    "acc = [100*i for i in acc]\n",
    "x = []\n",
    "count = 0\n",
    "for i in range(3):\n",
    "  for j in range(3):\n",
    "    x.append([kernels[(j+3)%3], feat_rep[i], acc[count]])\n",
    "    count += 1\n",
    "f = pd.DataFrame(x,columns=['kernels', 'Feature_Representation', 'Accuracy'])\n",
    "f.pivot('kernels','Feature_Representation','Accuracy').plot(kind='bar', figsize =(15,8), yticks=range(0,110,10), ylim=(0,130))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RCfa1UOtHdQZ"
   },
   "source": [
    "**We find that 3 sequence of calls produce slightly better results than 2 sequence of call while boolean occurence of calls performs much better in all kernels across all feature represenataions. Polynomail kernels perform better on an average across all kernels.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "K_veVeMWbvdb"
   },
   "source": [
    "### **3. Feature Importance :**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CdfhPmraoUvd"
   },
   "source": [
    "**Occurence of calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "vDoTh16IksmY"
   },
   "outputs": [],
   "source": [
    "#I have used bigram representations rather than trigram because of almost similar results\n",
    "#Also the bigrams are light on the session while triagrams use a lot of resources\n",
    "\n",
    "#Performing preprocessing on the original dataset based on occurence of calls\n",
    "vectorizer = CountVectorizer(ngram_range=(2,2))\n",
    "X = vectorizer.fit_transform(df.Calls)\n",
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "x = normalize(x)\n",
    "y = df_new['Class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RTSWU4I1ksmb",
    "outputId": "be98398e-a4be-4291-fca6-2ca5557bfb38"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,\n",
       "                     criterion='gini', max_depth=None, max_features='auto',\n",
       "                     max_leaf_nodes=None, max_samples=None,\n",
       "                     min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                     min_samples_leaf=1, min_samples_split=2,\n",
       "                     min_weight_fraction_leaf=0.0, n_estimators=100,\n",
       "                     n_jobs=None, oob_score=False, random_state=None, verbose=0,\n",
       "                     warm_start=False)"
      ]
     },
     "execution_count": 70,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Using Tree based Classifier for identifying important features\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "mdl = ExtraTreesClassifier()\n",
    "mdl.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "enIHJcbHksmd",
    "outputId": "d55cb608-65a5-4c9f-d837-50eefd6e2d70"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Feature</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>write read</td>\n",
       "      <td>0.075796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1816</th>\n",
       "      <td>read write</td>\n",
       "      <td>0.050759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1206</th>\n",
       "      <td>madvise ioctl</td>\n",
       "      <td>0.038980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1785</th>\n",
       "      <td>read madvise</td>\n",
       "      <td>0.031332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1800</th>\n",
       "      <td>read read</td>\n",
       "      <td>0.026438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2320</th>\n",
       "      <td>write futex</td>\n",
       "      <td>0.025188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1783</th>\n",
       "      <td>read ioctl</td>\n",
       "      <td>0.017367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>dup write</td>\n",
       "      <td>0.013781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2339</th>\n",
       "      <td>write munmap</td>\n",
       "      <td>0.012503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>write recvfrom</td>\n",
       "      <td>0.011827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2327</th>\n",
       "      <td>write getuid</td>\n",
       "      <td>0.009506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1019</th>\n",
       "      <td>getuid recvfrom</td>\n",
       "      <td>0.008948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1805</th>\n",
       "      <td>read rt_sigprocmask</td>\n",
       "      <td>0.008850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1107</th>\n",
       "      <td>ioctl getuid</td>\n",
       "      <td>0.008848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>futex getuid</td>\n",
       "      <td>0.008636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>madvise write</td>\n",
       "      <td>0.008472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948</th>\n",
       "      <td>rt_sigprocmask rt_sigprocmask</td>\n",
       "      <td>0.008458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2363</th>\n",
       "      <td>write write</td>\n",
       "      <td>0.008453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>mmap mmap</td>\n",
       "      <td>0.006475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>dup dup</td>\n",
       "      <td>0.006380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1018</th>\n",
       "      <td>getuid read</td>\n",
       "      <td>0.006239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1072</th>\n",
       "      <td>inotify_init1 mmap</td>\n",
       "      <td>0.006169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1788</th>\n",
       "      <td>read mmap</td>\n",
       "      <td>0.006029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>dup mmap</td>\n",
       "      <td>0.005430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>clock_gettime clock_gettime</td>\n",
       "      <td>0.005420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>mmap fstat</td>\n",
       "      <td>0.005378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>close write</td>\n",
       "      <td>0.005176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308</th>\n",
       "      <td>write dup</td>\n",
       "      <td>0.005017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>futex epoll_ctl</td>\n",
       "      <td>0.004960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1096</th>\n",
       "      <td>ioctl futex</td>\n",
       "      <td>0.004793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1483</th>\n",
       "      <td>munmap pread</td>\n",
       "      <td>0.004638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>mprotect dup</td>\n",
       "      <td>0.004594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>mmap prctl</td>\n",
       "      <td>0.004530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735</th>\n",
       "      <td>futex ioctl</td>\n",
       "      <td>0.004293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1110</th>\n",
       "      <td>ioctl ioctl</td>\n",
       "      <td>0.004196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>prctl mprotect</td>\n",
       "      <td>0.004103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>munmap munmap</td>\n",
       "      <td>0.004018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>getuid epoll_pwait</td>\n",
       "      <td>0.003966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1526</th>\n",
       "      <td>newfstatat ioctl</td>\n",
       "      <td>0.003897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2341</th>\n",
       "      <td>write openat</td>\n",
       "      <td>0.003778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1273</th>\n",
       "      <td>mmap close</td>\n",
       "      <td>0.003775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1144</th>\n",
       "      <td>ioctl write</td>\n",
       "      <td>0.003700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1604</th>\n",
       "      <td>openat write</td>\n",
       "      <td>0.003338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1642</th>\n",
       "      <td>prctl munmap</td>\n",
       "      <td>0.003255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1299</th>\n",
       "      <td>mmap munmap</td>\n",
       "      <td>0.003237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1453</th>\n",
       "      <td>munmap faccessat</td>\n",
       "      <td>0.003139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>munmap fstat</td>\n",
       "      <td>0.003097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1649</th>\n",
       "      <td>prctl readlinkat</td>\n",
       "      <td>0.003073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1392</th>\n",
       "      <td>mprotect mprotect</td>\n",
       "      <td>0.003046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2114</th>\n",
       "      <td>sendto writev</td>\n",
       "      <td>0.002992</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Feature     Score\n",
       "2346                     write read  0.075796\n",
       "1816                     read write  0.050759\n",
       "1206                  madvise ioctl  0.038980\n",
       "1785                   read madvise  0.031332\n",
       "1800                      read read  0.026438\n",
       "2320                    write futex  0.025188\n",
       "1783                     read ioctl  0.017367\n",
       "250                       dup write  0.013781\n",
       "2339                   write munmap  0.012503\n",
       "2348                 write recvfrom  0.011827\n",
       "2327                   write getuid  0.009506\n",
       "1019                getuid recvfrom  0.008948\n",
       "1805            read rt_sigprocmask  0.008850\n",
       "1107                   ioctl getuid  0.008848\n",
       "732                    futex getuid  0.008636\n",
       "1236                  madvise write  0.008472\n",
       "1948  rt_sigprocmask rt_sigprocmask  0.008458\n",
       "2363                    write write  0.008453\n",
       "1296                      mmap mmap  0.006475\n",
       "217                         dup dup  0.006380\n",
       "1018                    getuid read  0.006239\n",
       "1072             inotify_init1 mmap  0.006169\n",
       "1788                      read mmap  0.006029\n",
       "234                        dup mmap  0.005430\n",
       "22      clock_gettime clock_gettime  0.005420\n",
       "1282                     mmap fstat  0.005378\n",
       "200                     close write  0.005176\n",
       "2308                      write dup  0.005017\n",
       "709                 futex epoll_ctl  0.004960\n",
       "1096                    ioctl futex  0.004793\n",
       "1483                   munmap pread  0.004638\n",
       "1360                   mprotect dup  0.004594\n",
       "1303                     mmap prctl  0.004530\n",
       "735                     futex ioctl  0.004293\n",
       "1110                    ioctl ioctl  0.004196\n",
       "1641                 prctl mprotect  0.004103\n",
       "1478                  munmap munmap  0.004018\n",
       "993              getuid epoll_pwait  0.003966\n",
       "1526               newfstatat ioctl  0.003897\n",
       "2341                   write openat  0.003778\n",
       "1273                     mmap close  0.003775\n",
       "1144                    ioctl write  0.003700\n",
       "1604                   openat write  0.003338\n",
       "1642                   prctl munmap  0.003255\n",
       "1299                    mmap munmap  0.003237\n",
       "1453               munmap faccessat  0.003139\n",
       "1458                   munmap fstat  0.003097\n",
       "1649               prctl readlinkat  0.003073\n",
       "1392              mprotect mprotect  0.003046\n",
       "2114                  sendto writev  0.002992"
      ]
     },
     "execution_count": 71,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Viewing the most important feaetures along with scores in the dataset\n",
    "data ={'Feature':[],'Score':[]}\n",
    "for i,v in zip(mdl.feature_importances_,df_new.columns[1:]):\n",
    "  data['Score'].append(i)\n",
    "  data['Feature'].append(v)\n",
    "res = pd.DataFrame(data).sort_values('Score',ascending=False).head(50)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 536
    },
    "id": "y86uuxLGksmf",
    "outputId": "e3cd6172-ba18-4606-8bdc-82431b274a6c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 72,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the important features against theie scores\n",
    "(res.plot(kind='bar',figsize=(15,6)).set_xticklabels(res['Feature']))[0:0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ug-s_-GdoAfZ"
   },
   "source": [
    "**TF-IDF :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "seZ3AiNzjpwN"
   },
   "outputs": [],
   "source": [
    "#Performing preprocessing on the original dataset based on TF-IDF values\n",
    "vectorizer = TfidfVectorizer(ngram_range=(2,2))\n",
    "X = vectorizer.fit_transform(df.Calls)\n",
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "P3dTvoK_jpwQ",
    "outputId": "b48056b7-41d9-46a0-cf47-93f8fc8d0821"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,\n",
       "                     criterion='gini', max_depth=None, max_features='auto',\n",
       "                     max_leaf_nodes=None, max_samples=None,\n",
       "                     min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                     min_samples_leaf=1, min_samples_split=2,\n",
       "                     min_weight_fraction_leaf=0.0, n_estimators=100,\n",
       "                     n_jobs=None, oob_score=False, random_state=None, verbose=0,\n",
       "                     warm_start=False)"
      ]
     },
     "execution_count": 74,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "mdl = ExtraTreesClassifier()\n",
    "mdl.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "iiZtTReVjpwS",
    "outputId": "12bff2b7-0b70-424c-88d9-8454ccc183b6"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Feature</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>write read</td>\n",
       "      <td>0.049977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1800</th>\n",
       "      <td>read read</td>\n",
       "      <td>0.044360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1206</th>\n",
       "      <td>madvise ioctl</td>\n",
       "      <td>0.036912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1785</th>\n",
       "      <td>read madvise</td>\n",
       "      <td>0.034624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1816</th>\n",
       "      <td>read write</td>\n",
       "      <td>0.030494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1783</th>\n",
       "      <td>read ioctl</td>\n",
       "      <td>0.020318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2320</th>\n",
       "      <td>write futex</td>\n",
       "      <td>0.016334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2327</th>\n",
       "      <td>write getuid</td>\n",
       "      <td>0.014298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>dup write</td>\n",
       "      <td>0.011969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2348</th>\n",
       "      <td>write recvfrom</td>\n",
       "      <td>0.010548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1788</th>\n",
       "      <td>read mmap</td>\n",
       "      <td>0.009723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1019</th>\n",
       "      <td>getuid recvfrom</td>\n",
       "      <td>0.008864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>mmap prctl</td>\n",
       "      <td>0.008471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>dup dup</td>\n",
       "      <td>0.008066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>close write</td>\n",
       "      <td>0.007885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1236</th>\n",
       "      <td>madvise write</td>\n",
       "      <td>0.007847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>futex getuid</td>\n",
       "      <td>0.006978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1096</th>\n",
       "      <td>ioctl futex</td>\n",
       "      <td>0.006460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948</th>\n",
       "      <td>rt_sigprocmask rt_sigprocmask</td>\n",
       "      <td>0.006331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2339</th>\n",
       "      <td>write munmap</td>\n",
       "      <td>0.006288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735</th>\n",
       "      <td>futex ioctl</td>\n",
       "      <td>0.006146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2363</th>\n",
       "      <td>write write</td>\n",
       "      <td>0.006089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>close close</td>\n",
       "      <td>0.006047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1018</th>\n",
       "      <td>getuid read</td>\n",
       "      <td>0.005849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>clock_gettime clock_gettime</td>\n",
       "      <td>0.005675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1805</th>\n",
       "      <td>read rt_sigprocmask</td>\n",
       "      <td>0.005629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>mmap fstat</td>\n",
       "      <td>0.005523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1144</th>\n",
       "      <td>ioctl write</td>\n",
       "      <td>0.005487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>futex epoll_pwait</td>\n",
       "      <td>0.005199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1025</th>\n",
       "      <td>getuid sendto</td>\n",
       "      <td>0.004908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>futex epoll_ctl</td>\n",
       "      <td>0.004881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387</th>\n",
       "      <td>faccessat pread</td>\n",
       "      <td>0.004862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1107</th>\n",
       "      <td>ioctl getuid</td>\n",
       "      <td>0.004846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1110</th>\n",
       "      <td>ioctl ioctl</td>\n",
       "      <td>0.004724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1072</th>\n",
       "      <td>inotify_init1 mmap</td>\n",
       "      <td>0.004697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>munmap munmap</td>\n",
       "      <td>0.004552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1642</th>\n",
       "      <td>prctl munmap</td>\n",
       "      <td>0.004547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>close munmap</td>\n",
       "      <td>0.004538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>munmap fstat</td>\n",
       "      <td>0.004481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>getuid futex</td>\n",
       "      <td>0.004382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2108</th>\n",
       "      <td>sendto sendto</td>\n",
       "      <td>0.004236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>epoll_pwait write</td>\n",
       "      <td>0.004098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1392</th>\n",
       "      <td>mprotect mprotect</td>\n",
       "      <td>0.003891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1388</th>\n",
       "      <td>mprotect madvise</td>\n",
       "      <td>0.003872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>epoll_pwait getuid</td>\n",
       "      <td>0.003850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>prctl mprotect</td>\n",
       "      <td>0.003844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>mprotect dup</td>\n",
       "      <td>0.003844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>getuid epoll_pwait</td>\n",
       "      <td>0.003780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\n",
       "      <td>futex write</td>\n",
       "      <td>0.003773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308</th>\n",
       "      <td>write dup</td>\n",
       "      <td>0.003691</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Feature     Score\n",
       "2346                     write read  0.049977\n",
       "1800                      read read  0.044360\n",
       "1206                  madvise ioctl  0.036912\n",
       "1785                   read madvise  0.034624\n",
       "1816                     read write  0.030494\n",
       "1783                     read ioctl  0.020318\n",
       "2320                    write futex  0.016334\n",
       "2327                   write getuid  0.014298\n",
       "250                       dup write  0.011969\n",
       "2348                 write recvfrom  0.010548\n",
       "1788                      read mmap  0.009723\n",
       "1019                getuid recvfrom  0.008864\n",
       "1303                     mmap prctl  0.008471\n",
       "217                         dup dup  0.008066\n",
       "200                     close write  0.007885\n",
       "1236                  madvise write  0.007847\n",
       "732                    futex getuid  0.006978\n",
       "1096                    ioctl futex  0.006460\n",
       "1948  rt_sigprocmask rt_sigprocmask  0.006331\n",
       "2339                   write munmap  0.006288\n",
       "735                     futex ioctl  0.006146\n",
       "2363                    write write  0.006089\n",
       "137                     close close  0.006047\n",
       "1018                    getuid read  0.005849\n",
       "22      clock_gettime clock_gettime  0.005675\n",
       "1805            read rt_sigprocmask  0.005629\n",
       "1282                     mmap fstat  0.005523\n",
       "1144                    ioctl write  0.005487\n",
       "710               futex epoll_pwait  0.005199\n",
       "1025                  getuid sendto  0.004908\n",
       "709                 futex epoll_ctl  0.004881\n",
       "387                 faccessat pread  0.004862\n",
       "1107                   ioctl getuid  0.004846\n",
       "1110                    ioctl ioctl  0.004724\n",
       "1072             inotify_init1 mmap  0.004697\n",
       "1478                  munmap munmap  0.004552\n",
       "1642                   prctl munmap  0.004547\n",
       "174                    close munmap  0.004538\n",
       "1458                   munmap fstat  0.004481\n",
       "1000                   getuid futex  0.004382\n",
       "2108                  sendto sendto  0.004236\n",
       "349               epoll_pwait write  0.004098\n",
       "1392              mprotect mprotect  0.003891\n",
       "1388               mprotect madvise  0.003872\n",
       "320              epoll_pwait getuid  0.003850\n",
       "1641                 prctl mprotect  0.003844\n",
       "1360                   mprotect dup  0.003844\n",
       "993              getuid epoll_pwait  0.003780\n",
       "779                     futex write  0.003773\n",
       "2308                      write dup  0.003691"
      ]
     },
     "execution_count": 75,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data ={'Feature':[],'Score':[]}\n",
    "for i,v in zip(mdl.feature_importances_,df_new.columns[1:]):\n",
    "  data['Score'].append(i)\n",
    "  data['Feature'].append(v)\n",
    "res = pd.DataFrame(data).sort_values('Score',ascending=False).head(50)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 536
    },
    "id": "2rs0NZLhjpwU",
    "outputId": "a431d35e-7632-41a2-9c2f-3d81c35868ad"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 76,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(res.plot(kind='bar',figsize=(15,6)).set_xticklabels(res['Feature']))[0:0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FSas8Stpjvtq"
   },
   "source": [
    "**Boolean Occurence of Calls :**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "4e0vNwP-NZGf"
   },
   "outputs": [],
   "source": [
    "#Performing preprocessing on the original dataset based on boolean occurence of calls\n",
    "vectorizer = CountVectorizer(ngram_range=(2,2),binary=True)\n",
    "X = vectorizer.fit_transform(df.Calls)\n",
    "df1 = pd.DataFrame(pd.DataFrame(X.toarray(), columns = vectorizer.get_feature_names()))\n",
    "df1.index = df.index\n",
    "df_new = df.drop(columns=['Calls'])\n",
    "df_new = pd.concat([df_new,df1], axis = 1)\n",
    "features = list(df_new.columns)\n",
    "features.remove('Class')\n",
    "x = df_new[features]\n",
    "y = df_new['Class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "B-y8j8tgNRqp",
    "outputId": "32bfd321-6d21-4b72-9c75-8b31508acc1d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,\n",
       "                     criterion='gini', max_depth=None, max_features='auto',\n",
       "                     max_leaf_nodes=None, max_samples=None,\n",
       "                     min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                     min_samples_leaf=1, min_samples_split=2,\n",
       "                     min_weight_fraction_leaf=0.0, n_estimators=100,\n",
       "                     n_jobs=None, oob_score=False, random_state=None, verbose=0,\n",
       "                     warm_start=False)"
      ]
     },
     "execution_count": 78,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "mdl = ExtraTreesClassifier()\n",
    "mdl.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "1iSGVVJufkh6",
    "outputId": "7d112aeb-1fc7-42fe-b2f9-b0c73c28085c"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Feature</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1785</th>\n",
       "      <td>read madvise</td>\n",
       "      <td>0.034644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2308</th>\n",
       "      <td>write dup</td>\n",
       "      <td>0.027850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1213</th>\n",
       "      <td>madvise mprotect</td>\n",
       "      <td>0.026230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709</th>\n",
       "      <td>futex epoll_ctl</td>\n",
       "      <td>0.025961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>mprotect dup</td>\n",
       "      <td>0.025550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>dup write</td>\n",
       "      <td>0.024902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1388</th>\n",
       "      <td>mprotect madvise</td>\n",
       "      <td>0.022424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1805</th>\n",
       "      <td>read rt_sigprocmask</td>\n",
       "      <td>0.021744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>close newfstatat</td>\n",
       "      <td>0.017183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1788</th>\n",
       "      <td>read mmap</td>\n",
       "      <td>0.016343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>dup dup</td>\n",
       "      <td>0.016025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1101</th>\n",
       "      <td>ioctl getpriority</td>\n",
       "      <td>0.015785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>epoll_pwait futex</td>\n",
       "      <td>0.015112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>dup futex</td>\n",
       "      <td>0.013941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2339</th>\n",
       "      <td>write munmap</td>\n",
       "      <td>0.012835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1642</th>\n",
       "      <td>prctl munmap</td>\n",
       "      <td>0.012353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2341</th>\n",
       "      <td>write openat</td>\n",
       "      <td>0.011023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1018</th>\n",
       "      <td>getuid read</td>\n",
       "      <td>0.010926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1474</th>\n",
       "      <td>munmap mmap</td>\n",
       "      <td>0.010461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>futex epoll_pwait</td>\n",
       "      <td>0.010315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1100</th>\n",
       "      <td>ioctl getppid</td>\n",
       "      <td>0.009596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1116</th>\n",
       "      <td>ioctl mprotect</td>\n",
       "      <td>0.009076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2320</th>\n",
       "      <td>write futex</td>\n",
       "      <td>0.008413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1841</th>\n",
       "      <td>recvfrom futex</td>\n",
       "      <td>0.008093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>futex mprotect</td>\n",
       "      <td>0.007464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>getuid mprotect</td>\n",
       "      <td>0.007442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>732</th>\n",
       "      <td>futex getuid</td>\n",
       "      <td>0.006786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2077</th>\n",
       "      <td>sendto futex</td>\n",
       "      <td>0.006708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1394</th>\n",
       "      <td>mprotect munmap</td>\n",
       "      <td>0.006584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>prctl mprotect</td>\n",
       "      <td>0.006506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>getuid futex</td>\n",
       "      <td>0.006372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>758</th>\n",
       "      <td>futex recvfrom</td>\n",
       "      <td>0.006357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1303</th>\n",
       "      <td>mmap prctl</td>\n",
       "      <td>0.006344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>munmap munmap</td>\n",
       "      <td>0.006039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1289</th>\n",
       "      <td>mmap getuid</td>\n",
       "      <td>0.006022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2344</th>\n",
       "      <td>write pread</td>\n",
       "      <td>0.005937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870</th>\n",
       "      <td>getpriority ioctl</td>\n",
       "      <td>0.005865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>779</th>\n",
       "      <td>futex write</td>\n",
       "      <td>0.005676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2313</th>\n",
       "      <td>write fcntl</td>\n",
       "      <td>0.005280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707</th>\n",
       "      <td>futex dup</td>\n",
       "      <td>0.005109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>mmap mmap</td>\n",
       "      <td>0.005021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>epoll_pwait mprotect</td>\n",
       "      <td>0.004908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1678</th>\n",
       "      <td>pread munmap</td>\n",
       "      <td>0.004565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1604</th>\n",
       "      <td>openat write</td>\n",
       "      <td>0.004396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2336</th>\n",
       "      <td>write mprotect</td>\n",
       "      <td>0.004375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1821</th>\n",
       "      <td>readlinkat munmap</td>\n",
       "      <td>0.004302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>clone mprotect</td>\n",
       "      <td>0.004252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1649</th>\n",
       "      <td>prctl readlinkat</td>\n",
       "      <td>0.003917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1639</th>\n",
       "      <td>prctl mmap</td>\n",
       "      <td>0.003873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>309</th>\n",
       "      <td>epoll_pwait fcntl</td>\n",
       "      <td>0.003792</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Feature     Score\n",
       "1785          read madvise  0.034644\n",
       "2308             write dup  0.027850\n",
       "1213      madvise mprotect  0.026230\n",
       "709        futex epoll_ctl  0.025961\n",
       "1360          mprotect dup  0.025550\n",
       "250              dup write  0.024902\n",
       "1388      mprotect madvise  0.022424\n",
       "1805   read rt_sigprocmask  0.021744\n",
       "175       close newfstatat  0.017183\n",
       "1788             read mmap  0.016343\n",
       "217                dup dup  0.016025\n",
       "1101     ioctl getpriority  0.015785\n",
       "314      epoll_pwait futex  0.015112\n",
       "224              dup futex  0.013941\n",
       "2339          write munmap  0.012835\n",
       "1642          prctl munmap  0.012353\n",
       "2341          write openat  0.011023\n",
       "1018           getuid read  0.010926\n",
       "1474           munmap mmap  0.010461\n",
       "710      futex epoll_pwait  0.010315\n",
       "1100         ioctl getppid  0.009596\n",
       "1116        ioctl mprotect  0.009076\n",
       "2320           write futex  0.008413\n",
       "1841        recvfrom futex  0.008093\n",
       "742         futex mprotect  0.007464\n",
       "1010       getuid mprotect  0.007442\n",
       "732           futex getuid  0.006786\n",
       "2077          sendto futex  0.006708\n",
       "1394       mprotect munmap  0.006584\n",
       "1641        prctl mprotect  0.006506\n",
       "1000          getuid futex  0.006372\n",
       "758         futex recvfrom  0.006357\n",
       "1303            mmap prctl  0.006344\n",
       "1478         munmap munmap  0.006039\n",
       "1289           mmap getuid  0.006022\n",
       "2344           write pread  0.005937\n",
       "870      getpriority ioctl  0.005865\n",
       "779            futex write  0.005676\n",
       "2313           write fcntl  0.005280\n",
       "707              futex dup  0.005109\n",
       "1296             mmap mmap  0.005021\n",
       "328   epoll_pwait mprotect  0.004908\n",
       "1678          pread munmap  0.004565\n",
       "1604          openat write  0.004396\n",
       "2336        write mprotect  0.004375\n",
       "1821     readlinkat munmap  0.004302\n",
       "110         clone mprotect  0.004252\n",
       "1649      prctl readlinkat  0.003917\n",
       "1639            prctl mmap  0.003873\n",
       "309      epoll_pwait fcntl  0.003792"
      ]
     },
     "execution_count": 79,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data ={'Feature':[],'Score':[]}\n",
    "for i,v in zip(mdl.feature_importances_,df_new.columns[1:]):\n",
    "  data['Score'].append(i)\n",
    "  data['Feature'].append(v)\n",
    "res = pd.DataFrame(data).sort_values('Score',ascending=False).head(50)\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 486
    },
    "id": "YBP6Hm9LQzur",
    "outputId": "8a759b0d-a892-4b10-e5e0-9dfb5ca0d51e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 80,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(res.plot(kind='bar',figsize=(15,6)).set_xticklabels(res['Feature']))[0:0]"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "Assignment 4-5.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}