Iris_Flowers_Classification_ML_Project.ipynb

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      "source": [
        "#**IRIS FLOWER CLASSIFICATION**"
      ],
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      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " **Exploratory Data Analysis (EDA)**"
      ],
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      "source": [
        "columns = ['Sepal length','Sepal width','Petal length','Petal width','Class']\n",
        "dataset = pd.read_csv(\"iris.data\",names=columns)\n",
        "dataset.reset_index(drop=\"True\")"
      ],
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              "     Sepal length  Sepal width  Petal length  Petal width           Class\n",
              "0             5.1          3.5           1.4          0.2     Iris-setosa\n",
              "1             4.9          3.0           1.4          0.2     Iris-setosa\n",
              "2             4.7          3.2           1.3          0.2     Iris-setosa\n",
              "3             4.6          3.1           1.5          0.2     Iris-setosa\n",
              "4             5.0          3.6           1.4          0.2     Iris-setosa\n",
              "..            ...          ...           ...          ...             ...\n",
              "145           6.7          3.0           5.2          2.3  Iris-virginica\n",
              "146           6.3          2.5           5.0          1.9  Iris-virginica\n",
              "147           6.5          3.0           5.2          2.0  Iris-virginica\n",
              "148           6.2          3.4           5.4          2.3  Iris-virginica\n",
              "149           5.9          3.0           5.1          1.8  Iris-virginica\n",
              "\n",
              "[150 rows x 5 columns]"
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              "      <td>Iris-setosa</td>\n",
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              "      <td>6.7</td>\n",
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              "      <td>Iris-virginica</td>\n",
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              "      <td>6.2</td>\n",
              "      <td>3.4</td>\n",
              "      <td>5.4</td>\n",
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              "      <td>Iris-virginica</td>\n",
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              "      <td>5.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>1.8</td>\n",
              "      <td>Iris-virginica</td>\n",
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              "   Sepal length  Sepal width  Petal length  Petal width        Class\n",
              "0           5.1          3.5           1.4          0.2  Iris-setosa\n",
              "1           4.9          3.0           1.4          0.2  Iris-setosa\n",
              "2           4.7          3.2           1.3          0.2  Iris-setosa\n",
              "3           4.6          3.1           1.5          0.2  Iris-setosa\n",
              "4           5.0          3.6           1.4          0.2  Iris-setosa"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.scatterplot(x='Sepal length',y='Sepal width',data=dataset,hue='Class')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "LWiZI8utHrnz",
        "outputId": "f7cd7281-c6c2-41b4-8c5d-6cd0659e1b30"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd245c8a190>"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.heatmap(data=dataset.corr(),annot=True)\n",
        "plt.xlabel('Predicted')\n",
        "plt.ylabel('Actual')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 518
        },
        "id": "1NZULjz0JREs",
        "outputId": "405a9b8b-2946-41d8-e863-dcf49a154e89"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(69.0, 0.5, 'Actual')"
            ]
          },
          "metadata": {},
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.histplot(data=dataset,bins=8,palette='Set2')\n",
        "plt.xlabel('Sepal/Petal length/width')\n",
        "plt.title('Count')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "v73FozRYJkOy",
        "outputId": "5eb6f591-ee45-4a06-abb3-e1045b5758c7"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Count')"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ],
            "image/png": 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JFbZh/XqeWL6x3c535vB+bdq/traWlStX8sYbbzBhwgRWrVrFzp07mTJlChdccAGTJ09m+/btLFq0iIkTJzJ48GCuvfZaduzYQc+ePbn77rsZMmRIq9raWxsXX3wxM2bMYO7cuWzbto3nn3+esWPH8s1vfhOA6dOn841vfINjjz2WYcOG0b17dz75yU8yd+5cFixYwFe/+lXuu+8+AO69916uueYaNm/ezPTp0/f6RPy3w+AlSZIOWkNDAz/96U85//zzmTZtGueccw533XUXmzdvZuTIkXz0ox/l5ptvZunSpfzDP/wDAK+99hoLFy6ka9euPProo9x0003NwedA9tUGNN5ZW758Od27d2fIkCFMmDCBLl268JWvfIWnn36aY445hnPOOYdhw4ZxxhlncNFFFzFmzBguvfTS3d7PkiVLeOihh5g6dSqPPvpou14vg5ckSWqz7du3U11dDTTe8brqqqs444wzmDt3LrfddhsAO3bsYP1enqq/ZcsWxo0bx9q1a4mINk1W/fDDD++zjXPPPZdevXoBcPLJJ7Nu3TpeeeUVPvKRj3DccccBcNlll/HLX/5yn+f/+Mc/DsCIESOor69vdV2tZfCSJElt1jTGq6WUEvfdd99bug0XL1682/KkSZMYNWoUc+bMob6+nrq6ula3u782unfv3rzcpUuXVk+63VLTOQ72+ANxcL0kSWoXH/vYx7j99ttJKQGwfPlyAI455hhef/315v22bNlC3759AZgxY0a7tLEvp512GgsWLOD3v/89DQ0Nu3Vp7llXDgYvSZLULiZNmsTOnTupqqpi6NChTJo0CYBRo0axevVqqqurmTVrFjfccAMTJ05k+PDhbb6rtK829qVv377cdNNNjBw5kjPPPJNBgwY1d0deccUV3HrrrQwfPpznn3/+4N50G0VTYjyU1dTUpEo/V0OdV0Sw64kHyi6jFF3OvISO8DtA0u7WrFnDSSed1Lw8YOBANuxlLNXB6j9gAOvXrWu385Vt69atHH300TQ0NDB27FjGjx/P2LFj2+Xce/4sACJiWUqpZm/7O8ZLkqQO7nAKSZUwZcoUHn30UXbs2MF5553HJZdcUlotBi9JknRYa/oE5KHAMV6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZLarEuXLlRXV3PKKadw2WWXsW3btn3uu2LFCh566KEDnnP+/PmMGTOmzbW8+OKLu8232FJdXR1Nj6T62te+1ry+vr6eU045pc1tvV0GL0mSOrhBAwYSEe32NWjAwAO22TRl0KpVq+jWrRvf/e5397lva4PXwXrve9/L7NmzD7hfy+BVFh8nIUlSB7duw3peW1Tfbud751mD2rR/bW0tK1eu5I033mDChAmsWrWKnTt3MmXKFC644AImT57M9u3bWbRoERMnTmTw4MFce+217Nixg549e3L33Xe/Ze7Fli688EK+/vWvU1VVxfDhwxk7diyTJ09m8uTJ9O/fn9GjRzNmzBhWrVrF9u3b+fSnP80zzzzDiSeeyPbt2wG48cYbmyf2Hjp0KNOmTWPXrl185jOf4cknn6Rv3748+OCD9OzZ8+1cugPyjpckSTpoDQ0N/PSnP+XUU09l2rRpnHPOOSxZsoR58+Zx/fXXs3PnTm6++WYuv/xyVqxYweWXX86JJ57IwoULWb58OTfffDM33XTTftuora1l4cKFbNmyha5du/LEE08AsHDhQs4+++zd9r3jjjs46qijWLNmDVOnTmXZsmUA3HLLLc136e655x4A1q5dy+c//3meffZZjj322N3mcawU73hJkqQ2a7p7BI3B6KqrruKMM85g7ty5zQ8s3bFjB+v3MpXRli1bGDduHGvXriUi2Llz537bqq2t5dvf/jaDBw/mwgsv5JFHHmHbtm385je/YciQIdTX1zfv+/jjj/OFL3wBgKqqKqqqqvZ53sGDBze/hxEjRux2nkoxeEmSpDZrunvUUkqJ++677y3dhosXL95tedKkSYwaNYo5c+ZQX19PXV3dfts67bTTWLp0Ke973/sYPXo0r7zyCt/73vcYMWLE23oP3bt3b37dpUuX5m7JSrKrUZIktYuPfexj3H777aSUAFi+fDkAxxxzDK+//nrzflu2bKFv374AzJgx44Dn7datG/379+fee+/l9NNPp7a2lttuu+0t3YwAZ599Nj/4wQ8AWLVqFStXrmzeduSRRx7w7lqlGbwkSVK7mDRpEjt37qSqqoqhQ4cyadIkAEaNGsXq1auprq5m1qxZ3HDDDUycOJHhw4fT0NDQqnPX1tbynve8h549e1JbW8vGjRupra19y36f+9zn2Lp1KyeddBKTJ0/e7a7Y1VdfTVVVFZ/61Kfa5w0fhGhKpYeympqa1PQMDqm9RQS7nnig7DJK0eXMS+gIvwMk7W7NmjWcdNJJzcuDBgxk3Ya3jqU6WAP7D6B+/bp2O9/hbM+fBUBELEsp1extf8d4SZLUwRmSOg67GiVJkjIxeEmSJGVi8JIkqQNyfGb5DuZnYPCSJKmD6dGjB6+++qrhq0QpJV599VV69OjRpuMcXC9JUgfTr18/Nm7cyKZNm8oupVPr0aMH/fr1a9MxBi9JkjqYI488ksGDB5ddhg6CXY2SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTCoWvCJiSESsaPH1WkR8MSKOi4hHImJt8f1dlapBkiTpUFKx4JVSei6lVJ1SqgZGANuAOcCNwGMppQ8CjxXLkiRJh71cXY3nAs+nlNYBFwMzi/UzgUsy1SBJklSqXHM1XgH8sHh9QkrppeL1b4ET9nZARFwNXA0wYMCAihfY2Q0aMJB1G9aXXYYkSYe1igeviOgGXARM3HNbSilFRNrbcSmlO4E7AWpqava6j9rPug3reW1RfdlllOKdZw0quwRJUieRo6vxAuDplNLviuXfRUQfgOL7yxlqkCRJKl2O4HUl/9XNCDAXGFe8Hgc8mKEGSZKk0lU0eEXEO4DRwP0tVt8CjI6ItcBHi2VJkqTDXkXHeKWU3gDevce6V2n8lKMkSVKn4pPrJUmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiZdyy5AUnm6HBFERNlllGZg//7Ur19fdhmSOhGDl9SJ7XozseuJB8ouozRdzryk7BIkdTJ2NUqSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIy8QGqktQJDRg4kA2d+Kn9/QcMYP26dWWXoU6oosErIo4Fvg+cAiRgPPAcMAsYBNQDn0gp/b6SdUiSdrdh/Xrm1j9TdhmluWjQsLJLUCdV6a7Gvwd+llI6ERgGrAFuBB5LKX0QeKxYliRJOuxVLHhFRC/gbGA6QErpDymlzcDFwMxit5mAk6VJkqROoZJ3vAYDm4C7I2J5RHw/It4BnJBSeqnY57fACRWsQZIk6ZBRyeDVFfgj4I6U0nDgDfboVkwpJRrHfr1FRFwdEUsjYummTZsqWKYkSVIelQxeG4GNKaXFxfJsGoPY7yKiD0Dx/eW9HZxSujOlVJNSqjn++OMrWKYkSVIeFQteKaXfAhsiYkix6lxgNTAXGFesGwc8WKkaJEmSDiWVfo7XBOCeiOgG/Br4NI1h78cRcRWwDvhEhWuQJEk6JFQ0eKWUVgA1e9l0biXblSRJOhQ5ZZAkSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTCo9V2OHMWjAQNZtWF92GZIk6TBm8Cqs27Ce1xbVl11Gad551qCyS5Ak6bBnV6MkSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZdK17AIkScotjjiCiCi7jFL0HzCA9evWlV1Gp2XwkiR1OunNN5lb/0zZZZTiokHDyi6hU7OrUZIkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKpGslTx4R9cDrwC6gIaVUExHHAbOAQUA98ImU0u8rWYckSdKhIMcdr1EppeqUUk2xfCPwWErpg8BjxbIkSdJhr4yuxouBmcXrmcAlJdQgSZKUXaWDVwIejohlEXF1se6ElNJLxevfAifs7cCIuDoilkbE0k2bNlW4TEmSpMqr6Bgv4KyU0gsR8R7gkYj4RcuNKaUUEWlvB6aU7gTuBKipqdnrPpIkSR1JRe94pZReKL6/DMwBRgK/i4g+AMX3lytZgyRJ0qGiYsErIt4REcc0vQbOA1YBc4FxxW7jgAcrVYMkSdKhpJJdjScAcyKiqZ0fpJR+FhH/Dvw4Iq4C1gGfqGANkiRJh4yKBa+U0q+BYXtZ/ypwbqXa1cE54oguvPOsQWWXIUnSYa3Sg+vVQbz55i7mPfhs2WWUYtTFQ8suQZLUSThlkCRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUSauCV0Sc2Zp1kiRJ2rfW3vG6vZXrJEmStA9d97cxIk4HzgCOj4jrWmx6J9ClkoVJkiQdbvYbvIBuwNHFfse0WP8acGmlipIkSToc7Td4pZQWAAsiYkZKaV2mmiRJkg5LB7rj1aR7RNwJDGp5TErpnEoUJUmSdDhqbfC6F/gu8H1gV+XKkSRJOny1Nng1pJTuqGglkiRJh7nWPk7inyLimojoExHHNX1VtDJJkqTDTGvveI0rvl/fYl0C3te+5UiSJB2+WhW8UkqDK12IJEnS4a5VwSsi/nRv61NK/6d9y5EkSTp8tbar8bQWr3sA5wJPAwYvSZKkVmptV+OElssRcSzwo4pUJEmSdJhq7R2vPb0BOO5LUocXEWWXIKkTae0Yr3+i8VOM0Dg59knAjytVlCTl8sTyjWWXUIozh/cruwSpU2rtHa/bWrxuANallDrnbytJkqSD1KoHqBaTZf8COAZ4F/CHShYlSZJ0OGpV8IqITwBLgMuATwCLI+LSShYmSZJ0uGltV+OXgdNSSi8DRMTxwKPA7EoVJkmSdLhp7VyNRzSFrsKrbThWkiRJtP6O188i4l+AHxbLlwMPVaYkSZKkw9N+g1dEfAA4IaV0fUR8HDir2PQUcE+li5MkSTqcHOiO17eAiQAppfuB+wEi4tRi2/9T0eokSZIOIwcap3VCSunne64s1g2qSEWSJEmHqQMFr2P3s61naxqIiC4RsTwiflIsD46IxRHxq4iYFRHdWlusJElSR3ag4LU0Ij6z58qI+HNgWSvbuBZY02L5G8DfpZQ+APweuKqV55EkSerQDjTG64vAnIj4FP8VtGqAbsDYA508IvoBFwLTgOuicTbac4BPFrvMBKYAd7S5ckmSpA5mv8ErpfQ74IyIGAWcUqz+55TSv7by/N8CbqBxqiGAdwObU0oNxfJGoG/bSpYkSeqYWvUcr5TSPGBeW04cEWOAl1NKyyKirq2FRcTVwNUAAwYMaOvhkiRJh5xKPn3+TOCiiKgHfkRjF+PfA8dGRFPg6we8sLeDU0p3ppRqUko1xx9/fAXLlCRJyqNiwSulNDGl1C+lNAi4AvjXlNKnaLxz1jTB9jjgwUrVIEmSdCgpY77FL9E40P5XNI75ml5CDZIkSdm1dq7GtyWlNB+YX7z+NTAyR7uSJEmHkjLueEmSJHVKBi9JkqRMDF6SJEmZGLwkSZIyMXhJklQsi/IAABGySURBVCRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjLpWnYBkqRyTJ06tewSpE7H4CVJndT4v7iu7BJKs+zu+8suQZ2UXY2SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScqkYsErInpExJKIeCYino2IqcX6wRGxOCJ+FRGzIqJbpWqQJEk6lFTyjtd/AueklIYB1cD5EfFh4BvA36WUPgD8HriqgjVIkiQdMioWvFKjrcXikcVXAs4BZhfrZwKXVKoGSZKkQ0lFx3hFRJeIWAG8DDwCPA9sTik1FLtsBPru49irI2JpRCzdtGlTJcuUJEnKoqLBK6W0K6VUDfQDRgIntuHYO1NKNSmlmuOPP75iNUqSJOWS5VONKaXNwDzgdODYiOhabOoHvJCjBkmSpLJV8lONx0fEscXrnsBoYA2NAezSYrdxwIOVqkGSJOlQ0vXAuxy0PsDMiOhCY8D7cUrpJxGxGvhRRHwVWA5Mr2ANkiRJh4yKBa+U0kpg+F7W/5rG8V6SJEmdik+ulyRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZl0LbsA6VAwderUskuQJHUCBi8JmDj+2rJLKMXND/9Z2SVIUqdiV6MkSVImBi9JkqRMDF6SJEmZOMZLUqcVRxzBmcP7lV2GpE7E4CWp00pvvsk//tuisssoxec/fFbZJUidkl2NkiRJmRi8JEmSMjF4SZIkZWLwkiRJyqRiwSsi+kfEvIhYHRHPRsS1xfrjIuKRiFhbfH9XpWqQJEk6lFTyjlcD8L9SSicDHwY+HxEnAzcCj6WUPgg8VixLkiQd9ioWvFJKL6WUni5evw6sAfoCFwMzi91mApdUqgZJkqRDSZYxXhExCBgOLAZOSCm9VGz6LXBCjhokSZLKVvHgFRFHA/cBX0wpvdZyW0opAWkfx10dEUsjYummTZsqXaYkSVLFVTR4RcSRNIaue1JK9xerfxcRfYrtfYCX93ZsSunOlFJNSqnm+OOPr2SZkiRJWVTyU40BTAfWpJT+tsWmucC44vU44MFK1SBJknQoqeRcjWcCfwL8PCJWFOtuAm4BfhwRVwHrgE9UsAZJkqRDRsWCV0ppERD72HxupdqVJEk6VPnkekmSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpRJ17ILkCRJ+cQRRxARZZdRiv4DBrB+3bpSazB4SZLUiaQ332Ru/TNll1GKiwYNK7sEuxolSZJyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmfgAVUlSpzR16tSyS1AnZPCSJHVK4//iurJLKMWyu+8vu4ROrWJdjRFxV0S8HBGrWqw7LiIeiYi1xfd3Vap9SZKkQ00lx3jNAM7fY92NwGMppQ8CjxXLkiRJnULFgldK6XHgP/ZYfTEws3g9E7ikUu1LkiQdanKP8TohpfRS8fq3wAn72jEirgauBhgwYECG0qTOyQHGkpRPaYPrU0opItJ+tt8J3AlQU1Ozz/0kvT3j/+Kvyi6hNDc//KdllyCpk8n9HK/fRUQfgOL7y5nblyRJKk3u4DUXGFe8Hgc8mLl9SZKk0lTycRI/BJ4ChkTExoi4CrgFGB0Ra4GPFsuSJEmdQsXGeKWUrtzHpnMr1aYkSdKhzLkaJUmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEwMXpIkSZkYvCRJkjIxeEmSJGVi8JIkScrE4CVJkpSJwUuSJCkTg5ckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMuladgGSVKa7/r+/LbsESZ2IwUtSp3btJ8aWXUIp/vTu+8suQeqU7GqUJEnKxOAlSZKUicFLkiQpE4OXJElSJgYvSZKkTAxekiRJmRi8JEmSMjF4SZIkZWLwkiRJysTgJUmSlInBS5IkKRODlyRJUiYGL0mSpEy6ll3AoeKII7rwzrMGlV1GabocEYy6eGjZZZTm63f9fdklSJI6gVKCV0ScD/w90AX4fkrpljLqaOnNN3cx78Fnyy6jNKMuHsrzd32v7DJK8f7xn2HcFdeUXUYpbn74M2WXIEmdSvauxojoAvwjcAFwMnBlRJycuw5JkqTcyhjjNRL4VUrp1ymlPwA/Ai4uoQ5JkqSsyghefYENLZY3FuskSZIOa5FSyttgxKXA+SmlPy+W/wT445TSX+6x39XA1cXiEOC5diqhN/BKO52ro/IaeA3AawBeA/AagNcAvAbQvtdgYErp+L1tKGNw/QtA/xbL/Yp1u0kp3Qnc2d6NR8TSlFJNe5+3I/EaeA3AawBeA/AagNcAvAaQ7xqU0dX478AHI2JwRHQDrgDmllCHJElSVtnveKWUGiLiL4F/ofFxEnellDrvcxwkSVKnUcpzvFJKDwEPldE2Fei+7IC8Bl4D8BqA1wC8BuA1AK8BZLoG2QfXS5IkdVbO1ShJkpRJpwleEXF+RDwXEb+KiBvLrqcMEXFXRLwcEavKrqUMEdE/IuZFxOqIeDYiri27ptwiokdELImIZ4prMLXsmsoSEV0iYnlE/KTsWsoQEfUR8fOIWBERS8uupwwRcWxEzI6IX0TEmog4veyacouIIcW/gaav1yLii2XXlVNE/FXx+3BVRPwwInpUtL3O0NVYTFP0S2A0jQ9s/XfgypTS6lILyywizga2Av8npXRK2fXkFhF9gD4ppacj4hhgGXBJZ/p3EBEBvCOltDUijgQWAdemlP6t5NKyi4jrgBrgnSmlMWXXk1tE1AM1KaVO++ymiJgJLEwpfb/4lP1RKaXNZddVluJv5Qs0PltzXdn15BARfWn8PXhySml7RPwYeCilNKNSbXaWO15OUwSklB4H/qPsOsqSUnoppfR08fp1YA2dbNaE1GhrsXhk8XX4/+9rDxHRD7gQ+H7ZtagcEdELOBuYDpBS+kNnDl2Fc4HnO0voaqEr0DMiugJHAS9WsrHOErycpki7iYhBwHBgcbmV5Fd0sa0AXgYeSSl1umsAfAu4AXiz7EJKlICHI2JZMVNIZzMY2ATcXXQ5fz8i3lF2USW7Avhh2UXklFJ6AbgNWA+8BGxJKT1cyTY7S/CSmkXE0cB9wBdTSq+VXU9uKaVdKaVqGmeNGBkRnarbOSLGAC+nlJaVXUvJzkop/RFwAfD5YihCZ9IV+CPgjpTScOANoFOO/wUoulovAu4tu5acIuJdNPaADQbeC7wjIv5nJdvsLMGrVdMU6fBXjGu6D7gnpXR/2fWUqehWmQecX3YtmZ0JXFSMcfoRcE5E/N9yS8qv+J8+KaWXgTk0DsnoTDYCG1vc8Z1NYxDrrC4Ank4p/a7sQjL7KPCblNKmlNJO4H7gjEo22FmCl9MUqWlg+XRgTUrpb8uupwwRcXxEHFu87knjB05+UW5VeaWUJqaU+qWUBtH4u+BfU0oV/R/uoSYi3lF8wISie+08oFN92jml9FtgQ0QMKVadC3SaD9rsxZV0sm7GwnrgwxFxVPE34lwax/9WTClPrs/NaYoaRcQPgTqgd0RsBP4mpTS93KqyOhP4E+DnxRgngJuKmRQ6iz7AzOLTS0cAP04pdcrHKXRyJwBzGv/O0BX4QUrpZ+WWVIoJwD3Ff8h/DXy65HpKUYTv0cBflF1LbimlxRExG3gaaACWU+En2HeKx0lIkiQdCjpLV6MkSVLpDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnKxOAlqVlEfDkino2IlRGxIiL+uJ3PXxcRP2mxfGREPF283lW0uSoi7o2Io/ZznuqI+O9tbe9A69+uiLgkIk5usTw/Imr2s/+yiOjeivN+v+V5W6z/s4j4h4NpW1I5DF6SAIiI04ExwB+llKpofKLzhv0f9badBTxRvN6eUqpOKZ0C/AH47H6OqwYOGLxKcAnwloC0NxExGHghpfSfB9o3pfTnKaUDPdyz1W1LKo/BS1KTPsArTUEgpfRKSulFgIgYERELijs0/xIRfYr18yPi71vcqRpZrB8ZEU8Vkw8/2eLp4Hs6H/jpXtYvBD5QPGH9rohYUpzr4uJhlzcDlxftXt6G9t5ib20U6/8sIu6PiJ9FxNqI+GaLY66KiF8Wx3wvIv4hIs6gca67W4u63l/sflmx3y8jonaP9/6ziLgsIv62OO+1EfHr4vX7IuKJFte5pnj96aa2aXwoMAfRtqSSGLwkNXkY6F/8kf5ORHwEmue3vB24NKU0ArgLmNbiuKOKSbevKbZB4zREtcXkw5OBr+2jzVHA/JYrIqIrjfPG/Rz4Mo1T+ows9r0VOLI456ziDtmsNrS3N29po3iSNzTeWbscOJXGoNc/It4LTAI+TGPwOREgpfQkjVORXV/U9Xxxjq7Fub8I/E2Lds8HfkZjyGwKRbXAqxHRt3j9+B7Xpg8wtWj3LIo7XAfRtqSSdIopgyQdWEppa0SMoPEP/ihgVkTcCCwFTgEeKaaY6QK81OLQHxbHPx4R74zGuSCPoXFqog8CicawtJsiXPxHSmlbsapn/NdUTgtpnFfzSRontP7rYn0PYMBeyu91oPb247z9tPFYSmlLUe9qYCDQG1iQUvqPYv29wIf2c/6mydiXAYOKY7oB/VJKTXe3jo7GuRP7Az8Azqbx57DnRO5/DMxPKW0qjpvV1rYllcvgJalZSmkXjXeg5kfEz4FxNP7RfjaldPq+DtvL8leAeSmlsRExiD3uahXOp3H+1CbbiztnzaIx6f2PlNJze6zfc9B/a9rbl/210XL81S4O7ndm0zlaHl8LLGqxz5M0zhP4HI2hczxwOvC/DqK9A7UtqUR2NUoCICKGFHeMmlQD62gMA8cXg++bPok4tMV+lxfrzwK2FHeIegEvFNv/bB9N7mt8V0v/AkwoAhgRMbxY/zqNd9WatKa9traxL/8OfCQi3lV0i/6PFtv2rGtf9nzvC4G/prFrcTmNdxz/s+luWwuLi7bfXXQBX3YQbUsqkcFLUpOjaeyuWx0RK2kcPzQlpfQH4FLgGxHxDLACOKPFcTsiYjnwXeCqYt03ga8X699ypyUiugAfSCn94gA1fYXGbsOVEfFssQwwDzi5aXD9gdo7yDb2KqX0Ao1jyJbQ+InMeqApIP0IuL4YpP/+vZ8BgDpgQYvlhTR2Mz5e3HXcwO53xJrafgmYAjxVtL2mxebWti2pRJHSnr0EktQ6ETEf+OuU0tI2HncW8D9TSvt7ZMQhKyKOLsbEdQXmAHellOa08th+wPdSShdUtEhJhyT7/CVll1JaxF7u6HQgUyLiozQOxH8YeKC1B6aUNtL4qU1JnZB3vCRJkjJxjJckSVImBi9JkqRMDF6SJEmZGLwkSZIyMXhJkiRlYvCSJEnK5P8HtT2KBUidf2sAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig,axes = plt.subplots(figsize=(14,10),nrows=2,ncols=2)\n",
        "\n",
        "plt.suptitle('Distribution of Each Column')\n",
        "sns.kdeplot(data=dataset,x='Sepal length',hue='Class',shade=True,ax=axes[0][0])\n",
        "sns.kdeplot(data=dataset,x='Sepal width',hue='Class',shade=True,ax=axes[0][1])\n",
        "sns.kdeplot(data=dataset,x='Petal length',hue='Class',shade=True,ax=axes[1][0])\n",
        "sns.kdeplot(data=dataset,x='Petal width',hue='Class',shade=True,ax=axes[1][1])\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 729
        },
        "id": "iVpQ5EFlLHAu",
        "outputId": "dbf4b1c5-f323-47f9-e31f-b1604490dc46"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x720 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Logistic Regression**"
      ],
      "metadata": {
        "id": "Ao6Kl7ONMgdj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.model_selection import train_test_split "
      ],
      "metadata": {
        "id": "d1YE5BhwMjB7"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X = dataset.drop('Class',axis=1)\n",
        "y = dataset['Class']"
      ],
      "metadata": {
        "id": "9YmwwBTfMnxA"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "j4dMFay1NGXb",
        "outputId": "1623ab4b-cd93-4fab-e58b-64ddcc31b7fc"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Sepal length  Sepal width  Petal length  Petal width\n",
              "0             5.1          3.5           1.4          0.2\n",
              "1             4.9          3.0           1.4          0.2\n",
              "2             4.7          3.2           1.3          0.2\n",
              "3             4.6          3.1           1.5          0.2\n",
              "4             5.0          3.6           1.4          0.2\n",
              "..            ...          ...           ...          ...\n",
              "145           6.7          3.0           5.2          2.3\n",
              "146           6.3          2.5           5.0          1.9\n",
              "147           6.5          3.0           5.2          2.0\n",
              "148           6.2          3.4           5.4          2.3\n",
              "149           5.9          3.0           5.1          1.8\n",
              "\n",
              "[150 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-68a52885-4c88-4404-b06b-e155e7077b95\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Sepal length</th>\n",
              "      <th>Sepal width</th>\n",
              "      <th>Petal length</th>\n",
              "      <th>Petal width</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>6.7</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>2.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>6.3</td>\n",
              "      <td>2.5</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>6.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>6.2</td>\n",
              "      <td>3.4</td>\n",
              "      <td>5.4</td>\n",
              "      <td>2.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>5.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>1.8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-68a52885-4c88-4404-b06b-e155e7077b95')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-68a52885-4c88-4404-b06b-e155e7077b95 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-68a52885-4c88-4404-b06b-e155e7077b95');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ulc-PmRMNMP0",
        "outputId": "76d06513-d802-4bd3-ff79-7ba42b6029a6"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0         Iris-setosa\n",
              "1         Iris-setosa\n",
              "2         Iris-setosa\n",
              "3         Iris-setosa\n",
              "4         Iris-setosa\n",
              "            ...      \n",
              "145    Iris-virginica\n",
              "146    Iris-virginica\n",
              "147    Iris-virginica\n",
              "148    Iris-virginica\n",
              "149    Iris-virginica\n",
              "Name: Class, Length: 150, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2,random_state=42)\n",
        "X_train"
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      "metadata": {
        "colab": {
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          "height": 424
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        "id": "mMHUkavGNNAb",
        "outputId": "e86b78e8-ce48-49c7-e9db-e3ade2292071"
      },
      "execution_count": 13,
      "outputs": [
        {
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            "text/plain": [
              "     Sepal length  Sepal width  Petal length  Petal width\n",
              "22            4.6          3.6           1.0          0.2\n",
              "15            5.7          4.4           1.5          0.4\n",
              "65            6.7          3.1           4.4          1.4\n",
              "11            4.8          3.4           1.6          0.2\n",
              "42            4.4          3.2           1.3          0.2\n",
              "..            ...          ...           ...          ...\n",
              "71            6.1          2.8           4.0          1.3\n",
              "106           4.9          2.5           4.5          1.7\n",
              "14            5.8          4.0           1.2          0.2\n",
              "92            5.8          2.6           4.0          1.2\n",
              "102           7.1          3.0           5.9          2.1\n",
              "\n",
              "[120 rows x 4 columns]"
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              "      <th>Petal width</th>\n",
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              "      <th>22</th>\n",
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              "    <tr>\n",
              "      <th>106</th>\n",
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              "      <td>4.5</td>\n",
              "      <td>1.7</td>\n",
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              "      <th>14</th>\n",
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              "      <td>0.2</td>\n",
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              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>5.8</td>\n",
              "      <td>2.6</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.2</td>\n",
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              "    <tr>\n",
              "      <th>102</th>\n",
              "      <td>7.1</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.9</td>\n",
              "      <td>2.1</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>120 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ce3d06c2-003d-4d2c-9ade-3652a104f00b')\"\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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          "height": 206
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        "id": "qD-yuQbCNQqw",
        "outputId": "9d055d4c-fb7e-42f5-c403-f2db3df1bc50"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Sepal length  Sepal width  Petal length  Petal width\n",
              "73            6.1          2.8           4.7          1.2\n",
              "18            5.7          3.8           1.7          0.3\n",
              "118           7.7          2.6           6.9          2.3\n",
              "78            6.0          2.9           4.5          1.5\n",
              "76            6.8          2.8           4.8          1.4"
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              "      <td>4.5</td>\n",
              "      <td>1.5</td>\n",
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              "      <td>2.8</td>\n",
              "      <td>4.8</td>\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ec873482-ed49-4e5a-a91e-e6684e323d3a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ec873482-ed49-4e5a-a91e-e6684e323d3a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_test\n",
        "y_train"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HbuTbRm0NXe1",
        "outputId": "6810ff3d-4ca0-4a8e-9fc8-843908adb7bc"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "22         Iris-setosa\n",
              "15         Iris-setosa\n",
              "65     Iris-versicolor\n",
              "11         Iris-setosa\n",
              "42         Iris-setosa\n",
              "            ...       \n",
              "71     Iris-versicolor\n",
              "106     Iris-virginica\n",
              "14         Iris-setosa\n",
              "92     Iris-versicolor\n",
              "102     Iris-virginica\n",
              "Name: Class, Length: 120, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model = LogisticRegression()\n",
        "model.fit(X,y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vNgPYqkzNeOV",
        "outputId": "d8df9f36-94c0-4817-9848-acf4afe2a7be"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression()"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.coef_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8dRu-WOQNn-Z",
        "outputId": "5ac7c06a-dfb9-4882-e767-449c1bf7a4c3"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-0.42339954,  0.96170963, -2.5195144 , -1.08594123],\n",
              "       [ 0.53415033, -0.3179707 , -0.20537656, -0.93966834],\n",
              "       [-0.11075079, -0.64373893,  2.72489096,  2.02560957]])"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.intercept_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7bdJgvqCNop_",
        "outputId": "ddc9081c-7528-4f79-a6e1-d8f20a92c909"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([  9.88126443,   2.21931668, -12.1005811 ])"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = model.predict(X_test)\n",
        "y_pred"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6q3DyipZNsHT",
        "outputId": "e3437e4c-2b5f-47c1-bde5-f770c3d0af56"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Iris-versicolor', 'Iris-setosa', 'Iris-virginica',\n",
              "       'Iris-versicolor', 'Iris-versicolor', 'Iris-setosa',\n",
              "       'Iris-versicolor', 'Iris-virginica', 'Iris-versicolor',\n",
              "       'Iris-versicolor', 'Iris-virginica', 'Iris-setosa', 'Iris-setosa',\n",
              "       'Iris-setosa', 'Iris-setosa', 'Iris-versicolor', 'Iris-virginica',\n",
              "       'Iris-versicolor', 'Iris-versicolor', 'Iris-virginica',\n",
              "       'Iris-setosa', 'Iris-virginica', 'Iris-setosa', 'Iris-virginica',\n",
              "       'Iris-virginica', 'Iris-virginica', 'Iris-virginica',\n",
              "       'Iris-virginica', 'Iris-setosa', 'Iris-setosa'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import confusion_matrix"
      ],
      "metadata": {
        "id": "DAFfoY5LN0P7"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "conf = confusion_matrix(y_test,y_pred)\n",
        "conf"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qZQKBdrYN2xI",
        "outputId": "f501a8e6-6415-449c-a250-b2e1c9c20581"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[10,  0,  0],\n",
              "       [ 0,  9,  0],\n",
              "       [ 0,  0, 11]])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.heatmap(data=conf,annot=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "id": "brkvTVOfN5SL",
        "outputId": "4a71d8f6-7961-4a86-e160-4b32a58a0e6d"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fd24060bf10>"
            ]
          },
          "metadata": {},
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x576 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.get_params()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jQrAS4llN-Pw",
        "outputId": "f6ea6a27-a905-4b06-e5d6-240990406aa0"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'C': 1.0,\n",
              " 'class_weight': None,\n",
              " 'dual': False,\n",
              " 'fit_intercept': True,\n",
              " 'intercept_scaling': 1,\n",
              " 'l1_ratio': None,\n",
              " 'max_iter': 100,\n",
              " 'multi_class': 'auto',\n",
              " 'n_jobs': None,\n",
              " 'penalty': 'l2',\n",
              " 'random_state': None,\n",
              " 'solver': 'lbfgs',\n",
              " 'tol': 0.0001,\n",
              " 'verbose': 0,\n",
              " 'warm_start': False}"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ppTDwJKtPB6L",
        "outputId": "ec8fffdc-50dd-4107-97b9-7f33b6612c12"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Iris-versicolor', 'Iris-setosa', 'Iris-virginica',\n",
              "       'Iris-versicolor', 'Iris-versicolor', 'Iris-setosa',\n",
              "       'Iris-versicolor', 'Iris-virginica', 'Iris-versicolor',\n",
              "       'Iris-versicolor', 'Iris-virginica', 'Iris-setosa', 'Iris-setosa',\n",
              "       'Iris-setosa', 'Iris-setosa', 'Iris-versicolor', 'Iris-virginica',\n",
              "       'Iris-versicolor', 'Iris-versicolor', 'Iris-virginica',\n",
              "       'Iris-setosa', 'Iris-virginica', 'Iris-setosa', 'Iris-virginica',\n",
              "       'Iris-virginica', 'Iris-virginica', 'Iris-virginica',\n",
              "       'Iris-virginica', 'Iris-setosa', 'Iris-setosa'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_test"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YWt8arB_PDxg",
        "outputId": "a31fd484-0fc7-4a6f-afe3-4e2ba18fc4ea"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "73     Iris-versicolor\n",
              "18         Iris-setosa\n",
              "118     Iris-virginica\n",
              "78     Iris-versicolor\n",
              "76     Iris-versicolor\n",
              "31         Iris-setosa\n",
              "64     Iris-versicolor\n",
              "141     Iris-virginica\n",
              "68     Iris-versicolor\n",
              "82     Iris-versicolor\n",
              "110     Iris-virginica\n",
              "12         Iris-setosa\n",
              "36         Iris-setosa\n",
              "9          Iris-setosa\n",
              "19         Iris-setosa\n",
              "56     Iris-versicolor\n",
              "104     Iris-virginica\n",
              "69     Iris-versicolor\n",
              "55     Iris-versicolor\n",
              "132     Iris-virginica\n",
              "29         Iris-setosa\n",
              "127     Iris-virginica\n",
              "26         Iris-setosa\n",
              "128     Iris-virginica\n",
              "131     Iris-virginica\n",
              "145     Iris-virginica\n",
              "108     Iris-virginica\n",
              "143     Iris-virginica\n",
              "45         Iris-setosa\n",
              "30         Iris-setosa\n",
              "Name: Class, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Scores**"
      ],
      "metadata": {
        "id": "KZmChOkqQhFZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Score = \",model.score(X,y)*100,\"%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uJjM1mHhQFkT",
        "outputId": "966e4b5d-31e6-4ddc-aed1-83170ea2bf4a"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Score =  97.33333333333334 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Score = \",model.score(X_train,y_train)*100,\"%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ti-sMX2lQGYo",
        "outputId": "71fb51ea-e89e-4e64-b556-4ca9bd06b256"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Score =  96.66666666666667 %\n"
          ]
        }
      ]
    }
  ]
}