3_simulation_pfm.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"3_simulation_pfm.ipynb","provenance":[],"toc_visible":true,"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["#Predictive Failure Modelling Simulation"],"metadata":{"id":"ttN4X9SuAQ17"}},{"cell_type":"markdown","source":["##Configs"],"metadata":{"id":"zBIYmbNPAYTe"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"hhhU3png-DjJ","executionInfo":{"status":"ok","timestamp":1652034637227,"user_tz":240,"elapsed":22511,"user":{"displayName":"Luke Muther","userId":"09562218690618723932"}},"outputId":"bbc3ea49-a65f-4884-bd98-3d7a3893c553"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /gdrive\n","/gdrive/MyDrive/PredictiveModelling/data\n"]}],"source":["#Connecting to G Drive\n","from google.colab import drive\n","\n","drive.mount('/gdrive')\n","%cd /gdrive/MyDrive/ColabNotebooks/PredictiveModelling/data/"]},{"cell_type":"code","source":["import pandas as pd\n","import numpy as np\n","from xgboost import XGBClassifier\n","from sklearn import metrics"],"metadata":{"id":"XjTylnSs-LCK"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["all_data_df = pd.read_csv('combined_data.csv', index_col='Unnamed: 0')\n","all_data_df['datetime'] = pd.to_datetime(all_data_df['datetime']) #no formatting needed as it is already default style"],"metadata":{"id":"kaoK_nRw_XqI"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["all_data_df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":444},"id":"AhsQeU__YWMF","executionInfo":{"status":"ok","timestamp":1652034645489,"user_tz":240,"elapsed":21,"user":{"displayName":"Luke Muther","userId":"09562218690618723932"}},"outputId":"95185c36-7c8c-488f-82e1-79b003a5ac31"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["             datetime  machineID        volt      rotate    pressure  \\\n","0 2015-01-01 06:00:00          1  176.217853  418.504078  113.077935   \n","1 2015-01-01 07:00:00          1  162.879223  402.747490   95.460525   \n","2 2015-01-01 08:00:00          1  170.989902  527.349825   75.237905   \n","3 2015-01-01 09:00:00          1  162.462833  346.149335  109.248561   \n","4 2015-01-01 10:00:00          1  157.610021  435.376873  111.886648   \n","\n","   vibration     comp1     comp2     comp3     comp4  error1  error2  error3  \\\n","0  45.087686  0.000000  0.000000  0.000000  0.000000     NaN     NaN     NaN   \n","1  43.413973  0.041667  0.041667  0.041667  0.041667     NaN     NaN     NaN   \n","2  34.178847  0.083333  0.083333  0.083333  0.083333     NaN     NaN     NaN   \n","3  41.122144  0.125000  0.125000  0.125000  0.125000     NaN     NaN     NaN   \n","4  25.990511  0.166667  0.166667  0.166667  0.166667     NaN     NaN     NaN   \n","\n","   error4  error5 failure  \n","0     NaN     NaN     NaN  \n","1     NaN     NaN     NaN  \n","2     NaN     NaN     NaN  \n","3     NaN     NaN     NaN  \n","4     NaN     NaN     NaN  "],"text/html":["\n","  <div id=\"df-52f9f3ce-54c3-40b0-8663-955a01cf641c\">\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>datetime</th>\n","      <th>machineID</th>\n","      <th>volt</th>\n","      <th>rotate</th>\n","      <th>pressure</th>\n","      <th>vibration</th>\n","      <th>comp1</th>\n","      <th>comp2</th>\n","      <th>comp3</th>\n","      <th>comp4</th>\n","      <th>error1</th>\n","      <th>error2</th>\n","      <th>error3</th>\n","      <th>error4</th>\n","      <th>error5</th>\n","      <th>failure</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>2015-01-01 06:00:00</td>\n","      <td>1</td>\n","      <td>176.217853</td>\n","      <td>418.504078</td>\n","      <td>113.077935</td>\n","      <td>45.087686</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2015-01-01 07:00:00</td>\n","      <td>1</td>\n","      <td>162.879223</td>\n","      <td>402.747490</td>\n","      <td>95.460525</td>\n","      <td>43.413973</td>\n","      <td>0.041667</td>\n","      <td>0.041667</td>\n","      <td>0.041667</td>\n","      <td>0.041667</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2015-01-01 08:00:00</td>\n","      <td>1</td>\n","      <td>170.989902</td>\n","      <td>527.349825</td>\n","      <td>75.237905</td>\n","      <td>34.178847</td>\n","      <td>0.083333</td>\n","      <td>0.083333</td>\n","      <td>0.083333</td>\n","      <td>0.083333</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>2015-01-01 09:00:00</td>\n","      <td>1</td>\n","      <td>162.462833</td>\n","      <td>346.149335</td>\n","      <td>109.248561</td>\n","      <td>41.122144</td>\n","      <td>0.125000</td>\n","      <td>0.125000</td>\n","      <td>0.125000</td>\n","      <td>0.125000</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>2015-01-01 10:00:00</td>\n","      <td>1</td>\n","      <td>157.610021</td>\n","      <td>435.376873</td>\n","      <td>111.886648</td>\n","      <td>25.990511</td>\n","      <td>0.166667</td>\n","      <td>0.166667</td>\n","      <td>0.166667</td>\n","      <td>0.166667</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-52f9f3ce-54c3-40b0-8663-955a01cf641c')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n"," 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'block' : 'none';\n","\n","        async function convertToInteractive(key) {\n","          const element = document.querySelector('#df-52f9f3ce-54c3-40b0-8663-955a01cf641c');\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":4}]},{"cell_type":"markdown","source":["##Model to be used"],"metadata":{"id":"O-FDJOTTt2hq"}},{"cell_type":"code","source":["MAX_DEPTH = 4         #depth of trees\n","N_ESTIMATORS = 300    #number of trees\n","LEARNING_RATE = 0.08"],"metadata":{"id":"IQur7xkVt17o"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["model = XGBClassifier(\n","    silent = True,\n","    max_depth = MAX_DEPTH,\n","    n_estimators = N_ESTIMATORS,\n","    learning_rate = LEARNING_RATE,\n","    tree_method = 'hist',\n","    seed=8\n",")"],"metadata":{"id":"Earze_a-uN3F"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"DppC4w1dB1tM"},"source":["##Functions to get necessary stats from TS data"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"bQYGNjv4AnEc"},"outputs":[],"source":["tel_columns = [\"volt\", \"rotate\", \"pressure\", \"vibration\"]\n","error_columns = [\"error1\", \"error2\", \"error3\", \"error4\", \"error5\"]\n","maint_columns = [\"comp1\", \"comp2\", \"comp3\", \"comp4\"]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"J1PjY8ezAlHo"},"outputs":[],"source":["def validate_machine(df, lag_start, lag_length):\n","  if df['machineID'][lag_start-lag_length] == df['machineID'][lag_start]:\n","    return True\n","  else:\n","    return False"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"gAde5Qo-BrvG"},"outputs":[],"source":["def validate_datetime(df, lag_start, lag_length):\n","  if df['datetime'][lag_start-lag_length]+pd.Timedelta(str(lag_length)+' hours') == df['datetime'][lag_start]:\n","    return True\n","  else:\n","    return False"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"WRiCXvpEB-90"},"outputs":[],"source":["def get_stats(df, lag_start, lag_length):\n","  lag_df = df.iloc[lag_start-lag_length:lag_start+1]\n","  \n","  if not validate_machine(lag_df, lag_start, lag_length):\n","    raise ValueError('This DataFrame consists of data across different machines at index {} for {} hours of lag'.format(lag_start,lag_length))\n","  \n","  if not validate_datetime(lag_df, lag_start, lag_length):\n","    raise ValueError('The DataFrame does not contain {} hours of continuous data at index {}'.format(lag_length, lag_start))\n","  \n","  res = []\n","  for c in tel_columns:\n","    res.extend([\n","                lag_df[c].min(),\n","                lag_df[c].max(),\n","                lag_df[c].std(),\n","                lag_df[c].mean()\n","    ])\n","  \n","  for c in error_columns:\n","    res.append(lag_df[c].sum())\n","  \n","  for c in maint_columns:\n","    res.append(lag_df[c].iloc[-1])\n","\n","  return res"]},{"cell_type":"code","source":["#create column titles for statistics dataframe\n","col_titles = ['datetime']\n","for c in tel_columns:\n","  col_titles.append(c+'_min')\n","  col_titles.append(c+'_max')\n","  col_titles.append(c+'_std')\n","  col_titles.append(c+'_mean')\n","col_titles.extend(error_columns)\n","col_titles.extend(maint_columns)\n","\n","for c in col_titles.copy():\n","  if c != 'datetime':\n","    col_titles.append(c+'3')"],"metadata":{"id":"zr8JnxD4QRgw"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["##Simulation Setup"],"metadata":{"id":"WAA9pCqqGi92"}},{"cell_type":"code","source":["dti = pd.date_range(str(all_data_df['datetime'][0]+pd.Timedelta('7 days')), periods=51, freq=\"7D\")\n","dti[0:3]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"uEI410XzGsOo","executionInfo":{"status":"ok","timestamp":1652034645493,"user_tz":240,"elapsed":16,"user":{"displayName":"Luke Muther","userId":"09562218690618723932"}},"outputId":"6080ec6f-3b97-4452-b73a-3fc6855e652e"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["DatetimeIndex(['2015-01-08 06:00:00', '2015-01-15 06:00:00',\n","               '2015-01-22 06:00:00'],\n","              dtype='datetime64[ns]', freq='7D')"]},"metadata":{},"execution_count":12}]},{"cell_type":"code","source":["all_data_df['datetime'][[0,len(all_data_df)-1]]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cC4CqYnJMXn2","executionInfo":{"status":"ok","timestamp":1652034645494,"user_tz":240,"elapsed":15,"user":{"displayName":"Luke Muther","userId":"09562218690618723932"}},"outputId":"248511fe-cf0b-4947-8cb9-7bd474ca1441"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0        2015-01-01 06:00:00\n","876141   2016-01-01 06:00:00\n","Name: datetime, dtype: datetime64[ns]"]},"metadata":{},"execution_count":13}]},{"cell_type":"markdown","source":["###Function to create augmented dataframe based on selected date"],"metadata":{"id":"8iY8rOPxaXYX"}},{"cell_type":"code","source":["def get_augmented_df(df, date_string):\n","  augmented_df = df[df['datetime']<=date_string].reset_index(drop=True)\n","\n","  return augmented_df"],"metadata":{"id":"WAUfEZHbaz8-"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["###Function to capture machine failure statistics"],"metadata":{"id":"2X6AspVnaBdr"}},{"cell_type":"code","source":["def get_failure_statistics_df(df):\n","  lag_length = 24\n","  lag_length_short = 3\n","  predict_ahead = 12\n","  \n","  failures_indx = df.index[df['failure'].notnull()]\n","  \n","  failures_stats = []\n","\n","  for f in failures_indx:\n","    try:\n","      temp_ls = [df['datetime'][f-predict_ahead]]\n","      temp_ls.extend(get_stats(df, f-predict_ahead, lag_length))\n","      temp_ls.extend(get_stats(df, f-predict_ahead, lag_length_short))\n","      failures_stats.append(temp_ls)\n","    except Exception as e:\n","      None #print(e)\n","  \n","  failures_stats_df = pd.DataFrame(failures_stats, columns = col_titles)\n","  failures_stats_df['failure'] = True\n","\n","  return failures_stats_df"],"metadata":{"id":"EOn4cJQGbcPd"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"LHZzAjWBC1Sr"},"source":["###Function to create DataFrame with normal functioning machinery data"]},{"cell_type":"code","source":["def get_normal_statistics_df(df):\n","  lag_length = 24\n","  lag_length_short = 3\n","  predict_ahead = 12\n","  \n","  failures_indx = df.index[df['failure'].notnull()]\n","\n","  failure_indexes_plus = []\n","  for f in failures_indx:\n","    failure_indexes_plus.extend(np.arange(f-36,f+1))\n","  \n","  normal_indexes = df.drop(failure_indexes_plus).sample(len(df)//80, random_state=8).index\n","\n","  normal_stats = []\n","\n","  for n in normal_indexes:\n","    try:\n","      temp_ls = [df['datetime'][f-predict_ahead]]\n","      temp_ls.extend(get_stats(df, n-predict_ahead, lag_length))\n","      temp_ls.extend(get_stats(df, n-predict_ahead, lag_length_short))\n","      normal_stats.append(temp_ls)\n","    except Exception as e:\n","      None #print(e)\n","\n","  normal_stats_df = pd.DataFrame(normal_stats, columns = col_titles)\n","  normal_stats_df['failure'] = False\n","\n","  return normal_stats_df"],"metadata":{"id":"doOSlHXCcgyU"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"ifmXuTn4IZ3V"},"source":["###Function to combine DataFrames"]},{"cell_type":"code","source":["def combine_dataframes(failures, normals):\n","  total_stats_df = pd.concat([failures, normals], ignore_index=True)\n","\n","  #shuffle around DataFrame\n","  total_stats_df = total_stats_df.sample(len(total_stats_df), random_state=8)\n","\n","  return total_stats_df"],"metadata":{"id":"n9JlpXycfziV"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["###Function to split data"],"metadata":{"id":"WYU9T615wOY0"}},{"cell_type":"code","source":["def split_df(df):\n","  split_mask = np.random.rand(len(df)) < 0.8\n","\n","  x_df = df.drop(['datetime','failure'], axis=1)\n","  y_df = df['failure']\n","\n","  x_train = x_df[split_mask]\n","  y_train = y_df[split_mask]\n","\n","  x_validation = x_df[~split_mask]\n","  y_validation = y_df[~split_mask]\n","\n","  return x_train, y_train, x_validation, y_validation"],"metadata":{"id":"lxye_bBWwQdt"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["###Function to train model"],"metadata":{"id":"Wy4dbYe4wryD"}},{"cell_type":"code","source":["def train_model(model, x_train, y_train, x_validation, y_validation):\n","  model.fit(\n","    x_train, \n","    y_train, \n","    eval_set=[(x_validation, y_validation)], \n","    early_stopping_rounds=8, \n","    eval_metric=\"aucpr\"\n","  )\n","\n","  return model"],"metadata":{"id":"Rp-gAUx-wumj"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["###Function to test model"],"metadata":{"id":"UYATS0hZyHT2"}},{"cell_type":"code","source":["def test_model(model, df, old_date):\n","  temp_df = df[df['datetime']>old_date].reset_index(drop=True)\n","\n","  failure_df = get_failure_statistics_df(temp_df)\n","  normal_df = get_normal_statistics_df(temp_df)\n","  statistics_df = combine_dataframes(failure_df, normal_df)\n","  \n","  y_df = statistics_df['failure']\n","  x_df = statistics_df.drop(['datetime', 'failure'], axis=1)\n","\n","  test_predictions = model.predict(x_df)\n","  precision, recall, fscore, _ = metrics.precision_recall_fscore_support(y_df, test_predictions, average='weighted')\n","  confusion_matrix = metrics.confusion_matrix(y_df, test_predictions)\n","\n","  return precision, recall, fscore, confusion_matrix"],"metadata":{"id":"rQq_JHIEyJyC"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["##Simulation"],"metadata":{"id":"PZeyl4JWzAA4"}},{"cell_type":"code","source":["#31 min 15s\n","\n","simulation_data = []\n","error_log = ''\n","\n","for indx, date in enumerate(dti):\n","  print('Starting week {}\\n'.format(indx+1))\n","\n","  df = get_augmented_df(all_data_df, date)\n","  failure_df = get_failure_statistics_df(df)\n","  normal_df = get_normal_statistics_df(df)\n","  statistics_df = combine_dataframes(failure_df, normal_df)\n","\n","  x_train, y_train, x_validation, y_validation = split_df(statistics_df)\n","  \n","  if indx != 0:\n","    try:\n","      precision, recall, fscore, confusion_matrix = test_model(model, df, dti[indx-1])\n","\n","      pos_ratio = confusion_matrix[0][1]/confusion_matrix[1][1]\n","      false_pos = confusion_matrix[1][0]/confusion_matrix[1].sum()\n","\n","      simulation_data.append(['Week {}'.format(indx+1), training_points, precision, recall, fscore, confusion_matrix, pos_ratio, false_pos])\n","    except Exception as e:\n","      error_log += 'Error:\"' + str(e) + '\" at week {}'.format(indx+1) + '\\n'\n","\n","  model = train_model(model, x_train, y_train, x_validation, y_validation)\n","  \n","  training_points = len(x_train)\n","  \n","  print('\\nDone with week {}'.format(indx+1))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"uVxXttRCy-Uu","executionInfo":{"status":"ok","timestamp":1652037290224,"user_tz":240,"elapsed":1390126,"user":{"displayName":"Luke Muther","userId":"09562218690618723932"}},"outputId":"67ffdcaa-8d61-49f2-d839-9a463470e679"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Starting week 1\n","\n","[0]\tvalidation_0-aucpr:0.5\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.5\n","[2]\tvalidation_0-aucpr:0.5\n","[3]\tvalidation_0-aucpr:0.5\n","[4]\tvalidation_0-aucpr:0.5\n","[5]\tvalidation_0-aucpr:0.5\n","[6]\tvalidation_0-aucpr:0.5\n","[7]\tvalidation_0-aucpr:1\n","[8]\tvalidation_0-aucpr:1\n","[9]\tvalidation_0-aucpr:1\n","[10]\tvalidation_0-aucpr:1\n","[11]\tvalidation_0-aucpr:1\n","[12]\tvalidation_0-aucpr:1\n","[13]\tvalidation_0-aucpr:1\n","[14]\tvalidation_0-aucpr:1\n","[15]\tvalidation_0-aucpr:1\n","Stopping. Best iteration:\n","[7]\tvalidation_0-aucpr:1\n","\n","\n","Done with week 1\n","Starting week 2\n","\n","[0]\tvalidation_0-aucpr:0.57172\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.57172\n","[2]\tvalidation_0-aucpr:0.57172\n","[3]\tvalidation_0-aucpr:0.57172\n","[4]\tvalidation_0-aucpr:0.57172\n","[5]\tvalidation_0-aucpr:0.57172\n","[6]\tvalidation_0-aucpr:0.780278\n","[7]\tvalidation_0-aucpr:0.780278\n","[8]\tvalidation_0-aucpr:0.780278\n","[9]\tvalidation_0-aucpr:0.780278\n","[10]\tvalidation_0-aucpr:0.780278\n","[11]\tvalidation_0-aucpr:0.780278\n","[12]\tvalidation_0-aucpr:0.780278\n","[13]\tvalidation_0-aucpr:0.780278\n","[14]\tvalidation_0-aucpr:0.780278\n","Stopping. Best iteration:\n","[6]\tvalidation_0-aucpr:0.780278\n","\n","\n","Done with week 2\n","Starting week 3\n","\n","[0]\tvalidation_0-aucpr:0.852763\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.822376\n","[2]\tvalidation_0-aucpr:0.852763\n","[3]\tvalidation_0-aucpr:0.822376\n","[4]\tvalidation_0-aucpr:0.844059\n","[5]\tvalidation_0-aucpr:0.865055\n","[6]\tvalidation_0-aucpr:0.827865\n","[7]\tvalidation_0-aucpr:0.806868\n","[8]\tvalidation_0-aucpr:0.779918\n","[9]\tvalidation_0-aucpr:0.797464\n","[10]\tvalidation_0-aucpr:0.797464\n","[11]\tvalidation_0-aucpr:0.80505\n","[12]\tvalidation_0-aucpr:0.80505\n","[13]\tvalidation_0-aucpr:0.80505\n","Stopping. Best iteration:\n","[5]\tvalidation_0-aucpr:0.865055\n","\n","\n","Done with week 3\n","Starting week 4\n","\n","[0]\tvalidation_0-aucpr:0.737068\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.68895\n","[2]\tvalidation_0-aucpr:0.668355\n","[3]\tvalidation_0-aucpr:0.678712\n","[4]\tvalidation_0-aucpr:0.685874\n","[5]\tvalidation_0-aucpr:0.692908\n","[6]\tvalidation_0-aucpr:0.696465\n","[7]\tvalidation_0-aucpr:0.764724\n","[8]\tvalidation_0-aucpr:0.768921\n","[9]\tvalidation_0-aucpr:0.764724\n","[10]\tvalidation_0-aucpr:0.750527\n","[11]\tvalidation_0-aucpr:0.698279\n","[12]\tvalidation_0-aucpr:0.705159\n","[13]\tvalidation_0-aucpr:0.710926\n","[14]\tvalidation_0-aucpr:0.710352\n","[15]\tvalidation_0-aucpr:0.710352\n","[16]\tvalidation_0-aucpr:0.715123\n","Stopping. Best iteration:\n","[8]\tvalidation_0-aucpr:0.768921\n","\n","\n","Done with week 4\n","Starting week 5\n","\n","[0]\tvalidation_0-aucpr:0.692088\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.772112\n","[2]\tvalidation_0-aucpr:0.774965\n","[3]\tvalidation_0-aucpr:0.736238\n","[4]\tvalidation_0-aucpr:0.724536\n","[5]\tvalidation_0-aucpr:0.7306\n","[6]\tvalidation_0-aucpr:0.727783\n","[7]\tvalidation_0-aucpr:0.71947\n","[8]\tvalidation_0-aucpr:0.720716\n","[9]\tvalidation_0-aucpr:0.720716\n","[10]\tvalidation_0-aucpr:0.733628\n","Stopping. Best iteration:\n","[2]\tvalidation_0-aucpr:0.774965\n","\n","\n","Done with week 5\n","Starting week 6\n","\n","[0]\tvalidation_0-aucpr:0.901029\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.915729\n","[2]\tvalidation_0-aucpr:0.921534\n","[3]\tvalidation_0-aucpr:0.918512\n","[4]\tvalidation_0-aucpr:0.921534\n","[5]\tvalidation_0-aucpr:0.918512\n","[6]\tvalidation_0-aucpr:0.944195\n","[7]\tvalidation_0-aucpr:0.951664\n","[8]\tvalidation_0-aucpr:0.951025\n","[9]\tvalidation_0-aucpr:0.956299\n","[10]\tvalidation_0-aucpr:0.947241\n","[11]\tvalidation_0-aucpr:0.953123\n","[12]\tvalidation_0-aucpr:0.948873\n","[13]\tvalidation_0-aucpr:0.955031\n","[14]\tvalidation_0-aucpr:0.957135\n","[15]\tvalidation_0-aucpr:0.953921\n","[16]\tvalidation_0-aucpr:0.955029\n","[17]\tvalidation_0-aucpr:0.957497\n","[18]\tvalidation_0-aucpr:0.961986\n","[19]\tvalidation_0-aucpr:0.960367\n","[20]\tvalidation_0-aucpr:0.9622\n","[21]\tvalidation_0-aucpr:0.969086\n","[22]\tvalidation_0-aucpr:0.969086\n","[23]\tvalidation_0-aucpr:0.963538\n","[24]\tvalidation_0-aucpr:0.961052\n","[25]\tvalidation_0-aucpr:0.962997\n","[26]\tvalidation_0-aucpr:0.966712\n","[27]\tvalidation_0-aucpr:0.968331\n","[28]\tvalidation_0-aucpr:0.971549\n","[29]\tvalidation_0-aucpr:0.96888\n","[30]\tvalidation_0-aucpr:0.970221\n","[31]\tvalidation_0-aucpr:0.970049\n","[32]\tvalidation_0-aucpr:0.970049\n","[33]\tvalidation_0-aucpr:0.968603\n","[34]\tvalidation_0-aucpr:0.973232\n","[35]\tvalidation_0-aucpr:0.970221\n","[36]\tvalidation_0-aucpr:0.963682\n","[37]\tvalidation_0-aucpr:0.965444\n","[38]\tvalidation_0-aucpr:0.964103\n","[39]\tvalidation_0-aucpr:0.965444\n","[40]\tvalidation_0-aucpr:0.965444\n","[41]\tvalidation_0-aucpr:0.965482\n","[42]\tvalidation_0-aucpr:0.968691\n","Stopping. Best iteration:\n","[34]\tvalidation_0-aucpr:0.973232\n","\n","\n","Done with week 6\n","Starting week 7\n","\n","[0]\tvalidation_0-aucpr:0.626214\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.661092\n","[2]\tvalidation_0-aucpr:0.662455\n","[3]\tvalidation_0-aucpr:0.668025\n","[4]\tvalidation_0-aucpr:0.676199\n","[5]\tvalidation_0-aucpr:0.650725\n","[6]\tvalidation_0-aucpr:0.66025\n","[7]\tvalidation_0-aucpr:0.664457\n","[8]\tvalidation_0-aucpr:0.667057\n","[9]\tvalidation_0-aucpr:0.699827\n","[10]\tvalidation_0-aucpr:0.72976\n","[11]\tvalidation_0-aucpr:0.732315\n","[12]\tvalidation_0-aucpr:0.736593\n","[13]\tvalidation_0-aucpr:0.735245\n","[14]\tvalidation_0-aucpr:0.734417\n","[15]\tvalidation_0-aucpr:0.727178\n","[16]\tvalidation_0-aucpr:0.752524\n","[17]\tvalidation_0-aucpr:0.750651\n","[18]\tvalidation_0-aucpr:0.751738\n","[19]\tvalidation_0-aucpr:0.749941\n","[20]\tvalidation_0-aucpr:0.752007\n","[21]\tvalidation_0-aucpr:0.730609\n","[22]\tvalidation_0-aucpr:0.726501\n","[23]\tvalidation_0-aucpr:0.726501\n","[24]\tvalidation_0-aucpr:0.729317\n","Stopping. Best iteration:\n","[16]\tvalidation_0-aucpr:0.752524\n","\n","\n","Done with week 7\n","Starting week 8\n","\n","[0]\tvalidation_0-aucpr:0.752146\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.780306\n","[2]\tvalidation_0-aucpr:0.834474\n","[3]\tvalidation_0-aucpr:0.840146\n","[4]\tvalidation_0-aucpr:0.831826\n","[5]\tvalidation_0-aucpr:0.831772\n","[6]\tvalidation_0-aucpr:0.81023\n","[7]\tvalidation_0-aucpr:0.825836\n","[8]\tvalidation_0-aucpr:0.820164\n","[9]\tvalidation_0-aucpr:0.834277\n","[10]\tvalidation_0-aucpr:0.851666\n","[11]\tvalidation_0-aucpr:0.848243\n","[12]\tvalidation_0-aucpr:0.8476\n","[13]\tvalidation_0-aucpr:0.844946\n","[14]\tvalidation_0-aucpr:0.857857\n","[15]\tvalidation_0-aucpr:0.850821\n","[16]\tvalidation_0-aucpr:0.846482\n","[17]\tvalidation_0-aucpr:0.856108\n","[18]\tvalidation_0-aucpr:0.85119\n","[19]\tvalidation_0-aucpr:0.858314\n","[20]\tvalidation_0-aucpr:0.869322\n","[21]\tvalidation_0-aucpr:0.866792\n","[22]\tvalidation_0-aucpr:0.866824\n","[23]\tvalidation_0-aucpr:0.871081\n","[24]\tvalidation_0-aucpr:0.869664\n","[25]\tvalidation_0-aucpr:0.869285\n","[26]\tvalidation_0-aucpr:0.869772\n","[27]\tvalidation_0-aucpr:0.865694\n","[28]\tvalidation_0-aucpr:0.866411\n","[29]\tvalidation_0-aucpr:0.862331\n","[30]\tvalidation_0-aucpr:0.865105\n","[31]\tvalidation_0-aucpr:0.86746\n","Stopping. Best iteration:\n","[23]\tvalidation_0-aucpr:0.871081\n","\n","\n","Done with week 8\n","Starting week 9\n","\n","[0]\tvalidation_0-aucpr:0.910825\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.872735\n","[2]\tvalidation_0-aucpr:0.929951\n","[3]\tvalidation_0-aucpr:0.949143\n","[4]\tvalidation_0-aucpr:0.938627\n","[5]\tvalidation_0-aucpr:0.949619\n","[6]\tvalidation_0-aucpr:0.954411\n","[7]\tvalidation_0-aucpr:0.956115\n","[8]\tvalidation_0-aucpr:0.954729\n","[9]\tvalidation_0-aucpr:0.957743\n","[10]\tvalidation_0-aucpr:0.95729\n","[11]\tvalidation_0-aucpr:0.950422\n","[12]\tvalidation_0-aucpr:0.954078\n","[13]\tvalidation_0-aucpr:0.951511\n","[14]\tvalidation_0-aucpr:0.955519\n","[15]\tvalidation_0-aucpr:0.952746\n","[16]\tvalidation_0-aucpr:0.953702\n","[17]\tvalidation_0-aucpr:0.950929\n","Stopping. Best iteration:\n","[9]\tvalidation_0-aucpr:0.957743\n","\n","\n","Done with week 9\n","Starting week 10\n","\n","[0]\tvalidation_0-aucpr:0.701679\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.741213\n","[2]\tvalidation_0-aucpr:0.742554\n","[3]\tvalidation_0-aucpr:0.737944\n","[4]\tvalidation_0-aucpr:0.739933\n","[5]\tvalidation_0-aucpr:0.745356\n","[6]\tvalidation_0-aucpr:0.738698\n","[7]\tvalidation_0-aucpr:0.748781\n","[8]\tvalidation_0-aucpr:0.764741\n","[9]\tvalidation_0-aucpr:0.771377\n","[10]\tvalidation_0-aucpr:0.767943\n","[11]\tvalidation_0-aucpr:0.756548\n","[12]\tvalidation_0-aucpr:0.759291\n","[13]\tvalidation_0-aucpr:0.764444\n","[14]\tvalidation_0-aucpr:0.803841\n","[15]\tvalidation_0-aucpr:0.80119\n","[16]\tvalidation_0-aucpr:0.800924\n","[17]\tvalidation_0-aucpr:0.799369\n","[18]\tvalidation_0-aucpr:0.800421\n","[19]\tvalidation_0-aucpr:0.812743\n","[20]\tvalidation_0-aucpr:0.822392\n","[21]\tvalidation_0-aucpr:0.799834\n","[22]\tvalidation_0-aucpr:0.802586\n","[23]\tvalidation_0-aucpr:0.817567\n","[24]\tvalidation_0-aucpr:0.817201\n","[25]\tvalidation_0-aucpr:0.811406\n","[26]\tvalidation_0-aucpr:0.807908\n","[27]\tvalidation_0-aucpr:0.809541\n","[28]\tvalidation_0-aucpr:0.822405\n","[29]\tvalidation_0-aucpr:0.802457\n","[30]\tvalidation_0-aucpr:0.814024\n","[31]\tvalidation_0-aucpr:0.804591\n","[32]\tvalidation_0-aucpr:0.825071\n","[33]\tvalidation_0-aucpr:0.812419\n","[34]\tvalidation_0-aucpr:0.830873\n","[35]\tvalidation_0-aucpr:0.81246\n","[36]\tvalidation_0-aucpr:0.825967\n","[37]\tvalidation_0-aucpr:0.819709\n","[38]\tvalidation_0-aucpr:0.816852\n","[39]\tvalidation_0-aucpr:0.796147\n","[40]\tvalidation_0-aucpr:0.811506\n","[41]\tvalidation_0-aucpr:0.810561\n","[42]\tvalidation_0-aucpr:0.804937\n","Stopping. Best iteration:\n","[34]\tvalidation_0-aucpr:0.830873\n","\n","\n","Done with week 10\n","Starting week 11\n","\n","[0]\tvalidation_0-aucpr:0.60713\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.600518\n","[2]\tvalidation_0-aucpr:0.601299\n","[3]\tvalidation_0-aucpr:0.60221\n","[4]\tvalidation_0-aucpr:0.598776\n","[5]\tvalidation_0-aucpr:0.58867\n","[6]\tvalidation_0-aucpr:0.607419\n","[7]\tvalidation_0-aucpr:0.614461\n","[8]\tvalidation_0-aucpr:0.605213\n","[9]\tvalidation_0-aucpr:0.58394\n","[10]\tvalidation_0-aucpr:0.586735\n","[11]\tvalidation_0-aucpr:0.612685\n","[12]\tvalidation_0-aucpr:0.61166\n","[13]\tvalidation_0-aucpr:0.611328\n","[14]\tvalidation_0-aucpr:0.62456\n","[15]\tvalidation_0-aucpr:0.631643\n","[16]\tvalidation_0-aucpr:0.642268\n","[17]\tvalidation_0-aucpr:0.637799\n","[18]\tvalidation_0-aucpr:0.637522\n","[19]\tvalidation_0-aucpr:0.645854\n","[20]\tvalidation_0-aucpr:0.642242\n","[21]\tvalidation_0-aucpr:0.648527\n","[22]\tvalidation_0-aucpr:0.647595\n","[23]\tvalidation_0-aucpr:0.637316\n","[24]\tvalidation_0-aucpr:0.651314\n","[25]\tvalidation_0-aucpr:0.650547\n","[26]\tvalidation_0-aucpr:0.651365\n","[27]\tvalidation_0-aucpr:0.650718\n","[28]\tvalidation_0-aucpr:0.650718\n","[29]\tvalidation_0-aucpr:0.67427\n","[30]\tvalidation_0-aucpr:0.657841\n","[31]\tvalidation_0-aucpr:0.652017\n","[32]\tvalidation_0-aucpr:0.651511\n","[33]\tvalidation_0-aucpr:0.653908\n","[34]\tvalidation_0-aucpr:0.650556\n","[35]\tvalidation_0-aucpr:0.638197\n","[36]\tvalidation_0-aucpr:0.639824\n","[37]\tvalidation_0-aucpr:0.642699\n","Stopping. Best iteration:\n","[29]\tvalidation_0-aucpr:0.67427\n","\n","\n","Done with week 11\n","Starting week 12\n","\n","[0]\tvalidation_0-aucpr:0.731887\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.738445\n","[2]\tvalidation_0-aucpr:0.767357\n","[3]\tvalidation_0-aucpr:0.760508\n","[4]\tvalidation_0-aucpr:0.761299\n","[5]\tvalidation_0-aucpr:0.756693\n","[6]\tvalidation_0-aucpr:0.772083\n","[7]\tvalidation_0-aucpr:0.793467\n","[8]\tvalidation_0-aucpr:0.795037\n","[9]\tvalidation_0-aucpr:0.808123\n","[10]\tvalidation_0-aucpr:0.80939\n","[11]\tvalidation_0-aucpr:0.808101\n","[12]\tvalidation_0-aucpr:0.813426\n","[13]\tvalidation_0-aucpr:0.815878\n","[14]\tvalidation_0-aucpr:0.81661\n","[15]\tvalidation_0-aucpr:0.803134\n","[16]\tvalidation_0-aucpr:0.806834\n","[17]\tvalidation_0-aucpr:0.800651\n","[18]\tvalidation_0-aucpr:0.801881\n","[19]\tvalidation_0-aucpr:0.807711\n","[20]\tvalidation_0-aucpr:0.811231\n","[21]\tvalidation_0-aucpr:0.802598\n","[22]\tvalidation_0-aucpr:0.794997\n","Stopping. Best iteration:\n","[14]\tvalidation_0-aucpr:0.81661\n","\n","\n","Done with week 12\n","Starting week 13\n","\n","[0]\tvalidation_0-aucpr:0.814279\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.778136\n","[2]\tvalidation_0-aucpr:0.777193\n","[3]\tvalidation_0-aucpr:0.76701\n","[4]\tvalidation_0-aucpr:0.788926\n","[5]\tvalidation_0-aucpr:0.841242\n","[6]\tvalidation_0-aucpr:0.802068\n","[7]\tvalidation_0-aucpr:0.801671\n","[8]\tvalidation_0-aucpr:0.828674\n","[9]\tvalidation_0-aucpr:0.849577\n","[10]\tvalidation_0-aucpr:0.850917\n","[11]\tvalidation_0-aucpr:0.833739\n","[12]\tvalidation_0-aucpr:0.856176\n","[13]\tvalidation_0-aucpr:0.853124\n","[14]\tvalidation_0-aucpr:0.858179\n","[15]\tvalidation_0-aucpr:0.85966\n","[16]\tvalidation_0-aucpr:0.86302\n","[17]\tvalidation_0-aucpr:0.865405\n","[18]\tvalidation_0-aucpr:0.88502\n","[19]\tvalidation_0-aucpr:0.869615\n","[20]\tvalidation_0-aucpr:0.867646\n","[21]\tvalidation_0-aucpr:0.870916\n","[22]\tvalidation_0-aucpr:0.869703\n","[23]\tvalidation_0-aucpr:0.870588\n","[24]\tvalidation_0-aucpr:0.869894\n","[25]\tvalidation_0-aucpr:0.864265\n","[26]\tvalidation_0-aucpr:0.869438\n","Stopping. Best iteration:\n","[18]\tvalidation_0-aucpr:0.88502\n","\n","\n","Done with week 13\n","Starting week 14\n","\n","[0]\tvalidation_0-aucpr:0.876949\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.897423\n","[2]\tvalidation_0-aucpr:0.883606\n","[3]\tvalidation_0-aucpr:0.899705\n","[4]\tvalidation_0-aucpr:0.907583\n","[5]\tvalidation_0-aucpr:0.867505\n","[6]\tvalidation_0-aucpr:0.913331\n","[7]\tvalidation_0-aucpr:0.903144\n","[8]\tvalidation_0-aucpr:0.902042\n","[9]\tvalidation_0-aucpr:0.907693\n","[10]\tvalidation_0-aucpr:0.867348\n","[11]\tvalidation_0-aucpr:0.897084\n","[12]\tvalidation_0-aucpr:0.895167\n","[13]\tvalidation_0-aucpr:0.891739\n","[14]\tvalidation_0-aucpr:0.857721\n","Stopping. Best iteration:\n","[6]\tvalidation_0-aucpr:0.913331\n","\n","\n","Done with week 14\n","Starting week 15\n","\n","[0]\tvalidation_0-aucpr:0.837883\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.85739\n","[2]\tvalidation_0-aucpr:0.868958\n","[3]\tvalidation_0-aucpr:0.826555\n","[4]\tvalidation_0-aucpr:0.8198\n","[5]\tvalidation_0-aucpr:0.8182\n","[6]\tvalidation_0-aucpr:0.822686\n","[7]\tvalidation_0-aucpr:0.825246\n","[8]\tvalidation_0-aucpr:0.825139\n","[9]\tvalidation_0-aucpr:0.8076\n","[10]\tvalidation_0-aucpr:0.802052\n","Stopping. Best iteration:\n","[2]\tvalidation_0-aucpr:0.868958\n","\n","\n","Done with week 15\n","Starting week 16\n","\n","[0]\tvalidation_0-aucpr:0.786915\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.786915\n","[2]\tvalidation_0-aucpr:0.791\n","[3]\tvalidation_0-aucpr:0.797562\n","[4]\tvalidation_0-aucpr:0.797562\n","[5]\tvalidation_0-aucpr:0.819275\n","[6]\tvalidation_0-aucpr:0.808136\n","[7]\tvalidation_0-aucpr:0.808485\n","[8]\tvalidation_0-aucpr:0.804157\n","[9]\tvalidation_0-aucpr:0.820189\n","[10]\tvalidation_0-aucpr:0.81784\n","[11]\tvalidation_0-aucpr:0.82091\n","[12]\tvalidation_0-aucpr:0.825103\n","[13]\tvalidation_0-aucpr:0.844847\n","[14]\tvalidation_0-aucpr:0.840139\n","[15]\tvalidation_0-aucpr:0.847104\n","[16]\tvalidation_0-aucpr:0.845998\n","[17]\tvalidation_0-aucpr:0.853185\n","[18]\tvalidation_0-aucpr:0.844406\n","[19]\tvalidation_0-aucpr:0.849943\n","[20]\tvalidation_0-aucpr:0.852258\n","[21]\tvalidation_0-aucpr:0.871925\n","[22]\tvalidation_0-aucpr:0.871785\n","[23]\tvalidation_0-aucpr:0.874922\n","[24]\tvalidation_0-aucpr:0.876644\n","[25]\tvalidation_0-aucpr:0.898678\n","[26]\tvalidation_0-aucpr:0.902449\n","[27]\tvalidation_0-aucpr:0.898262\n","[28]\tvalidation_0-aucpr:0.902606\n","[29]\tvalidation_0-aucpr:0.899027\n","[30]\tvalidation_0-aucpr:0.904252\n","[31]\tvalidation_0-aucpr:0.902687\n","[32]\tvalidation_0-aucpr:0.906328\n","[33]\tvalidation_0-aucpr:0.904619\n","[34]\tvalidation_0-aucpr:0.903099\n","[35]\tvalidation_0-aucpr:0.903428\n","[36]\tvalidation_0-aucpr:0.90326\n","[37]\tvalidation_0-aucpr:0.905108\n","[38]\tvalidation_0-aucpr:0.906472\n","[39]\tvalidation_0-aucpr:0.906984\n","[40]\tvalidation_0-aucpr:0.90357\n","[41]\tvalidation_0-aucpr:0.904359\n","[42]\tvalidation_0-aucpr:0.904359\n","[43]\tvalidation_0-aucpr:0.906079\n","[44]\tvalidation_0-aucpr:0.899706\n","[45]\tvalidation_0-aucpr:0.902967\n","[46]\tvalidation_0-aucpr:0.905135\n","[47]\tvalidation_0-aucpr:0.903686\n","Stopping. Best iteration:\n","[39]\tvalidation_0-aucpr:0.906984\n","\n","\n","Done with week 16\n","Starting week 17\n","\n","[0]\tvalidation_0-aucpr:0.850347\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.855892\n","[2]\tvalidation_0-aucpr:0.854651\n","[3]\tvalidation_0-aucpr:0.853569\n","[4]\tvalidation_0-aucpr:0.84888\n","[5]\tvalidation_0-aucpr:0.851541\n","[6]\tvalidation_0-aucpr:0.851509\n","[7]\tvalidation_0-aucpr:0.846915\n","[8]\tvalidation_0-aucpr:0.847689\n","[9]\tvalidation_0-aucpr:0.857602\n","[10]\tvalidation_0-aucpr:0.867286\n","[11]\tvalidation_0-aucpr:0.868676\n","[12]\tvalidation_0-aucpr:0.876773\n","[13]\tvalidation_0-aucpr:0.860209\n","[14]\tvalidation_0-aucpr:0.882296\n","[15]\tvalidation_0-aucpr:0.883724\n","[16]\tvalidation_0-aucpr:0.885244\n","[17]\tvalidation_0-aucpr:0.883479\n","[18]\tvalidation_0-aucpr:0.883074\n","[19]\tvalidation_0-aucpr:0.901573\n","[20]\tvalidation_0-aucpr:0.903281\n","[21]\tvalidation_0-aucpr:0.902691\n","[22]\tvalidation_0-aucpr:0.902566\n","[23]\tvalidation_0-aucpr:0.903233\n","[24]\tvalidation_0-aucpr:0.906295\n","[25]\tvalidation_0-aucpr:0.903538\n","[26]\tvalidation_0-aucpr:0.902324\n","[27]\tvalidation_0-aucpr:0.902209\n","[28]\tvalidation_0-aucpr:0.900976\n","[29]\tvalidation_0-aucpr:0.901474\n","[30]\tvalidation_0-aucpr:0.895208\n","[31]\tvalidation_0-aucpr:0.899562\n","[32]\tvalidation_0-aucpr:0.899642\n","Stopping. Best iteration:\n","[24]\tvalidation_0-aucpr:0.906295\n","\n","\n","Done with week 17\n","Starting week 18\n","\n","[0]\tvalidation_0-aucpr:0.820873\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.822598\n","[2]\tvalidation_0-aucpr:0.832351\n","[3]\tvalidation_0-aucpr:0.849807\n","[4]\tvalidation_0-aucpr:0.843109\n","[5]\tvalidation_0-aucpr:0.8577\n","[6]\tvalidation_0-aucpr:0.86129\n","[7]\tvalidation_0-aucpr:0.893241\n","[8]\tvalidation_0-aucpr:0.900446\n","[9]\tvalidation_0-aucpr:0.90144\n","[10]\tvalidation_0-aucpr:0.896939\n","[11]\tvalidation_0-aucpr:0.899099\n","[12]\tvalidation_0-aucpr:0.899071\n","[13]\tvalidation_0-aucpr:0.912771\n","[14]\tvalidation_0-aucpr:0.911684\n","[15]\tvalidation_0-aucpr:0.91287\n","[16]\tvalidation_0-aucpr:0.911559\n","[17]\tvalidation_0-aucpr:0.915558\n","[18]\tvalidation_0-aucpr:0.915919\n","[19]\tvalidation_0-aucpr:0.926565\n","[20]\tvalidation_0-aucpr:0.927561\n","[21]\tvalidation_0-aucpr:0.932567\n","[22]\tvalidation_0-aucpr:0.935396\n","[23]\tvalidation_0-aucpr:0.935685\n","[24]\tvalidation_0-aucpr:0.939625\n","[25]\tvalidation_0-aucpr:0.941446\n","[26]\tvalidation_0-aucpr:0.943643\n","[27]\tvalidation_0-aucpr:0.945098\n","[28]\tvalidation_0-aucpr:0.946913\n","[29]\tvalidation_0-aucpr:0.946781\n","[30]\tvalidation_0-aucpr:0.946497\n","[31]\tvalidation_0-aucpr:0.948541\n","[32]\tvalidation_0-aucpr:0.947491\n","[33]\tvalidation_0-aucpr:0.947799\n","[34]\tvalidation_0-aucpr:0.946739\n","[35]\tvalidation_0-aucpr:0.94666\n","[36]\tvalidation_0-aucpr:0.948558\n","[37]\tvalidation_0-aucpr:0.945516\n","[38]\tvalidation_0-aucpr:0.945486\n","[39]\tvalidation_0-aucpr:0.947543\n","[40]\tvalidation_0-aucpr:0.947303\n","[41]\tvalidation_0-aucpr:0.944759\n","[42]\tvalidation_0-aucpr:0.94445\n","[43]\tvalidation_0-aucpr:0.943121\n","[44]\tvalidation_0-aucpr:0.942828\n","Stopping. Best iteration:\n","[36]\tvalidation_0-aucpr:0.948558\n","\n","\n","Done with week 18\n","Starting week 19\n","\n","[0]\tvalidation_0-aucpr:0.897293\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.897293\n","[2]\tvalidation_0-aucpr:0.909075\n","[3]\tvalidation_0-aucpr:0.906103\n","[4]\tvalidation_0-aucpr:0.925123\n","[5]\tvalidation_0-aucpr:0.9396\n","[6]\tvalidation_0-aucpr:0.944422\n","[7]\tvalidation_0-aucpr:0.946621\n","[8]\tvalidation_0-aucpr:0.961438\n","[9]\tvalidation_0-aucpr:0.959724\n","[10]\tvalidation_0-aucpr:0.96138\n","[11]\tvalidation_0-aucpr:0.959515\n","[12]\tvalidation_0-aucpr:0.959507\n","[13]\tvalidation_0-aucpr:0.957405\n","[14]\tvalidation_0-aucpr:0.957733\n","[15]\tvalidation_0-aucpr:0.955622\n","[16]\tvalidation_0-aucpr:0.955361\n","Stopping. Best iteration:\n","[8]\tvalidation_0-aucpr:0.961438\n","\n","\n","Done with week 19\n","Starting week 20\n","\n","[0]\tvalidation_0-aucpr:0.878657\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.873523\n","[2]\tvalidation_0-aucpr:0.873632\n","[3]\tvalidation_0-aucpr:0.907395\n","[4]\tvalidation_0-aucpr:0.929054\n","[5]\tvalidation_0-aucpr:0.931148\n","[6]\tvalidation_0-aucpr:0.939689\n","[7]\tvalidation_0-aucpr:0.939679\n","[8]\tvalidation_0-aucpr:0.940874\n","[9]\tvalidation_0-aucpr:0.944302\n","[10]\tvalidation_0-aucpr:0.94491\n","[11]\tvalidation_0-aucpr:0.943862\n","[12]\tvalidation_0-aucpr:0.940419\n","[13]\tvalidation_0-aucpr:0.943473\n","[14]\tvalidation_0-aucpr:0.940266\n","[15]\tvalidation_0-aucpr:0.93949\n","[16]\tvalidation_0-aucpr:0.940601\n","[17]\tvalidation_0-aucpr:0.939926\n","[18]\tvalidation_0-aucpr:0.939732\n","Stopping. Best iteration:\n","[10]\tvalidation_0-aucpr:0.94491\n","\n","\n","Done with week 20\n","Starting week 21\n","\n","[0]\tvalidation_0-aucpr:0.777016\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.786256\n","[2]\tvalidation_0-aucpr:0.781955\n","[3]\tvalidation_0-aucpr:0.784451\n","[4]\tvalidation_0-aucpr:0.783657\n","[5]\tvalidation_0-aucpr:0.781493\n","[6]\tvalidation_0-aucpr:0.786129\n","[7]\tvalidation_0-aucpr:0.785071\n","[8]\tvalidation_0-aucpr:0.785313\n","[9]\tvalidation_0-aucpr:0.786194\n","Stopping. Best iteration:\n","[1]\tvalidation_0-aucpr:0.786256\n","\n","\n","Done with week 21\n","Starting week 22\n","\n","[0]\tvalidation_0-aucpr:0.792055\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.806878\n","[2]\tvalidation_0-aucpr:0.796878\n","[3]\tvalidation_0-aucpr:0.789931\n","[4]\tvalidation_0-aucpr:0.782835\n","[5]\tvalidation_0-aucpr:0.790377\n","[6]\tvalidation_0-aucpr:0.792604\n","[7]\tvalidation_0-aucpr:0.787056\n","[8]\tvalidation_0-aucpr:0.78887\n","[9]\tvalidation_0-aucpr:0.789479\n","Stopping. Best iteration:\n","[1]\tvalidation_0-aucpr:0.806878\n","\n","\n","Done with week 22\n","Starting week 23\n","\n","[0]\tvalidation_0-aucpr:0.69962\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.714157\n","[2]\tvalidation_0-aucpr:0.720096\n","[3]\tvalidation_0-aucpr:0.766148\n","[4]\tvalidation_0-aucpr:0.802478\n","[5]\tvalidation_0-aucpr:0.802577\n","[6]\tvalidation_0-aucpr:0.808313\n","[7]\tvalidation_0-aucpr:0.803625\n","[8]\tvalidation_0-aucpr:0.809971\n","[9]\tvalidation_0-aucpr:0.810305\n","[10]\tvalidation_0-aucpr:0.81347\n","[11]\tvalidation_0-aucpr:0.806651\n","[12]\tvalidation_0-aucpr:0.805387\n","[13]\tvalidation_0-aucpr:0.80903\n","[14]\tvalidation_0-aucpr:0.810602\n","[15]\tvalidation_0-aucpr:0.804064\n","[16]\tvalidation_0-aucpr:0.80056\n","[17]\tvalidation_0-aucpr:0.822977\n","[18]\tvalidation_0-aucpr:0.793843\n","[19]\tvalidation_0-aucpr:0.789448\n","[20]\tvalidation_0-aucpr:0.815513\n","[21]\tvalidation_0-aucpr:0.795679\n","[22]\tvalidation_0-aucpr:0.796934\n","[23]\tvalidation_0-aucpr:0.798216\n","[24]\tvalidation_0-aucpr:0.817719\n","[25]\tvalidation_0-aucpr:0.815974\n","Stopping. Best iteration:\n","[17]\tvalidation_0-aucpr:0.822977\n","\n","\n","Done with week 23\n","Starting week 24\n","\n","[0]\tvalidation_0-aucpr:0.788875\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.798053\n","[2]\tvalidation_0-aucpr:0.794779\n","[3]\tvalidation_0-aucpr:0.77806\n","[4]\tvalidation_0-aucpr:0.773951\n","[5]\tvalidation_0-aucpr:0.775905\n","[6]\tvalidation_0-aucpr:0.787868\n","[7]\tvalidation_0-aucpr:0.784404\n","[8]\tvalidation_0-aucpr:0.805316\n","[9]\tvalidation_0-aucpr:0.804764\n","[10]\tvalidation_0-aucpr:0.808009\n","[11]\tvalidation_0-aucpr:0.805149\n","[12]\tvalidation_0-aucpr:0.809538\n","[13]\tvalidation_0-aucpr:0.812913\n","[14]\tvalidation_0-aucpr:0.812435\n","[15]\tvalidation_0-aucpr:0.811163\n","[16]\tvalidation_0-aucpr:0.802247\n","[17]\tvalidation_0-aucpr:0.839088\n","[18]\tvalidation_0-aucpr:0.831518\n","[19]\tvalidation_0-aucpr:0.836634\n","[20]\tvalidation_0-aucpr:0.840631\n","[21]\tvalidation_0-aucpr:0.841804\n","[22]\tvalidation_0-aucpr:0.833488\n","[23]\tvalidation_0-aucpr:0.836248\n","[24]\tvalidation_0-aucpr:0.842218\n","[25]\tvalidation_0-aucpr:0.842767\n","[26]\tvalidation_0-aucpr:0.851458\n","[27]\tvalidation_0-aucpr:0.852481\n","[28]\tvalidation_0-aucpr:0.860941\n","[29]\tvalidation_0-aucpr:0.860666\n","[30]\tvalidation_0-aucpr:0.864727\n","[31]\tvalidation_0-aucpr:0.863534\n","[32]\tvalidation_0-aucpr:0.86754\n","[33]\tvalidation_0-aucpr:0.871633\n","[34]\tvalidation_0-aucpr:0.870357\n","[35]\tvalidation_0-aucpr:0.876794\n","[36]\tvalidation_0-aucpr:0.876503\n","[37]\tvalidation_0-aucpr:0.874944\n","[38]\tvalidation_0-aucpr:0.876321\n","[39]\tvalidation_0-aucpr:0.876497\n","[40]\tvalidation_0-aucpr:0.872384\n","[41]\tvalidation_0-aucpr:0.876457\n","[42]\tvalidation_0-aucpr:0.876139\n","[43]\tvalidation_0-aucpr:0.872912\n","Stopping. Best iteration:\n","[35]\tvalidation_0-aucpr:0.876794\n","\n","\n","Done with week 24\n","Starting week 25\n","\n","[0]\tvalidation_0-aucpr:0.81541\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.813276\n","[2]\tvalidation_0-aucpr:0.825988\n","[3]\tvalidation_0-aucpr:0.846131\n","[4]\tvalidation_0-aucpr:0.83516\n","[5]\tvalidation_0-aucpr:0.844917\n","[6]\tvalidation_0-aucpr:0.83414\n","[7]\tvalidation_0-aucpr:0.830047\n","[8]\tvalidation_0-aucpr:0.846183\n","[9]\tvalidation_0-aucpr:0.852255\n","[10]\tvalidation_0-aucpr:0.879668\n","[11]\tvalidation_0-aucpr:0.884029\n","[12]\tvalidation_0-aucpr:0.879999\n","[13]\tvalidation_0-aucpr:0.875477\n","[14]\tvalidation_0-aucpr:0.867222\n","[15]\tvalidation_0-aucpr:0.877548\n","[16]\tvalidation_0-aucpr:0.870119\n","[17]\tvalidation_0-aucpr:0.871492\n","[18]\tvalidation_0-aucpr:0.872482\n","[19]\tvalidation_0-aucpr:0.869863\n","Stopping. Best iteration:\n","[11]\tvalidation_0-aucpr:0.884029\n","\n","\n","Done with week 25\n","Starting week 26\n","\n","[0]\tvalidation_0-aucpr:0.828593\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.846138\n","[2]\tvalidation_0-aucpr:0.8724\n","[3]\tvalidation_0-aucpr:0.873944\n","[4]\tvalidation_0-aucpr:0.876973\n","[5]\tvalidation_0-aucpr:0.874682\n","[6]\tvalidation_0-aucpr:0.882113\n","[7]\tvalidation_0-aucpr:0.880222\n","[8]\tvalidation_0-aucpr:0.891846\n","[9]\tvalidation_0-aucpr:0.88997\n","[10]\tvalidation_0-aucpr:0.892124\n","[11]\tvalidation_0-aucpr:0.899457\n","[12]\tvalidation_0-aucpr:0.899666\n","[13]\tvalidation_0-aucpr:0.896398\n","[14]\tvalidation_0-aucpr:0.896405\n","[15]\tvalidation_0-aucpr:0.896481\n","[16]\tvalidation_0-aucpr:0.8981\n","[17]\tvalidation_0-aucpr:0.897379\n","[18]\tvalidation_0-aucpr:0.890155\n","[19]\tvalidation_0-aucpr:0.888645\n","[20]\tvalidation_0-aucpr:0.888146\n","Stopping. Best iteration:\n","[12]\tvalidation_0-aucpr:0.899666\n","\n","\n","Done with week 26\n","Starting week 27\n","\n","[0]\tvalidation_0-aucpr:0.776138\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.773228\n","[2]\tvalidation_0-aucpr:0.792245\n","[3]\tvalidation_0-aucpr:0.807426\n","[4]\tvalidation_0-aucpr:0.813772\n","[5]\tvalidation_0-aucpr:0.834646\n","[6]\tvalidation_0-aucpr:0.830886\n","[7]\tvalidation_0-aucpr:0.835464\n","[8]\tvalidation_0-aucpr:0.835522\n","[9]\tvalidation_0-aucpr:0.834156\n","[10]\tvalidation_0-aucpr:0.831764\n","[11]\tvalidation_0-aucpr:0.832946\n","[12]\tvalidation_0-aucpr:0.832321\n","[13]\tvalidation_0-aucpr:0.832483\n","[14]\tvalidation_0-aucpr:0.834259\n","[15]\tvalidation_0-aucpr:0.832875\n","[16]\tvalidation_0-aucpr:0.833536\n","Stopping. Best iteration:\n","[8]\tvalidation_0-aucpr:0.835522\n","\n","\n","Done with week 27\n","Starting week 28\n","\n","[0]\tvalidation_0-aucpr:0.877293\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.877677\n","[2]\tvalidation_0-aucpr:0.900606\n","[3]\tvalidation_0-aucpr:0.900979\n","[4]\tvalidation_0-aucpr:0.905235\n","[5]\tvalidation_0-aucpr:0.912429\n","[6]\tvalidation_0-aucpr:0.904667\n","[7]\tvalidation_0-aucpr:0.903546\n","[8]\tvalidation_0-aucpr:0.902093\n","[9]\tvalidation_0-aucpr:0.918628\n","[10]\tvalidation_0-aucpr:0.91699\n","[11]\tvalidation_0-aucpr:0.919554\n","[12]\tvalidation_0-aucpr:0.917018\n","[13]\tvalidation_0-aucpr:0.908943\n","[14]\tvalidation_0-aucpr:0.906329\n","[15]\tvalidation_0-aucpr:0.902805\n","[16]\tvalidation_0-aucpr:0.901474\n","[17]\tvalidation_0-aucpr:0.903443\n","[18]\tvalidation_0-aucpr:0.906158\n","[19]\tvalidation_0-aucpr:0.910773\n","Stopping. Best iteration:\n","[11]\tvalidation_0-aucpr:0.919554\n","\n","\n","Done with week 28\n","Starting week 29\n","\n","[0]\tvalidation_0-aucpr:0.840067\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.851028\n","[2]\tvalidation_0-aucpr:0.848254\n","[3]\tvalidation_0-aucpr:0.847414\n","[4]\tvalidation_0-aucpr:0.847414\n","[5]\tvalidation_0-aucpr:0.821198\n","[6]\tvalidation_0-aucpr:0.822905\n","[7]\tvalidation_0-aucpr:0.817584\n","[8]\tvalidation_0-aucpr:0.817335\n","[9]\tvalidation_0-aucpr:0.82079\n","Stopping. Best iteration:\n","[1]\tvalidation_0-aucpr:0.851028\n","\n","\n","Done with week 29\n","Starting week 30\n","\n","[0]\tvalidation_0-aucpr:0.854162\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.853778\n","[2]\tvalidation_0-aucpr:0.860625\n","[3]\tvalidation_0-aucpr:0.871263\n","[4]\tvalidation_0-aucpr:0.868153\n","[5]\tvalidation_0-aucpr:0.865716\n","[6]\tvalidation_0-aucpr:0.871934\n","[7]\tvalidation_0-aucpr:0.889959\n","[8]\tvalidation_0-aucpr:0.890558\n","[9]\tvalidation_0-aucpr:0.891018\n","[10]\tvalidation_0-aucpr:0.892227\n","[11]\tvalidation_0-aucpr:0.892911\n","[12]\tvalidation_0-aucpr:0.890882\n","[13]\tvalidation_0-aucpr:0.893751\n","[14]\tvalidation_0-aucpr:0.896699\n","[15]\tvalidation_0-aucpr:0.896522\n","[16]\tvalidation_0-aucpr:0.894551\n","[17]\tvalidation_0-aucpr:0.893434\n","[18]\tvalidation_0-aucpr:0.898176\n","[19]\tvalidation_0-aucpr:0.904485\n","[20]\tvalidation_0-aucpr:0.90679\n","[21]\tvalidation_0-aucpr:0.902084\n","[22]\tvalidation_0-aucpr:0.904053\n","[23]\tvalidation_0-aucpr:0.912037\n","[24]\tvalidation_0-aucpr:0.910308\n","[25]\tvalidation_0-aucpr:0.906473\n","[26]\tvalidation_0-aucpr:0.906711\n","[27]\tvalidation_0-aucpr:0.905886\n","[28]\tvalidation_0-aucpr:0.903388\n","[29]\tvalidation_0-aucpr:0.899476\n","[30]\tvalidation_0-aucpr:0.899611\n","[31]\tvalidation_0-aucpr:0.903086\n","Stopping. Best iteration:\n","[23]\tvalidation_0-aucpr:0.912037\n","\n","\n","Done with week 30\n","Starting week 31\n","\n","[0]\tvalidation_0-aucpr:0.905269\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.909097\n","[2]\tvalidation_0-aucpr:0.906521\n","[3]\tvalidation_0-aucpr:0.90563\n","[4]\tvalidation_0-aucpr:0.907472\n","[5]\tvalidation_0-aucpr:0.907411\n","[6]\tvalidation_0-aucpr:0.897218\n","[7]\tvalidation_0-aucpr:0.899972\n","[8]\tvalidation_0-aucpr:0.905069\n","[9]\tvalidation_0-aucpr:0.896273\n","Stopping. Best iteration:\n","[1]\tvalidation_0-aucpr:0.909097\n","\n","\n","Done with week 31\n","Starting week 32\n","\n","[0]\tvalidation_0-aucpr:0.786612\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.782906\n","[2]\tvalidation_0-aucpr:0.785382\n","[3]\tvalidation_0-aucpr:0.784866\n","[4]\tvalidation_0-aucpr:0.796436\n","[5]\tvalidation_0-aucpr:0.795966\n","[6]\tvalidation_0-aucpr:0.79488\n","[7]\tvalidation_0-aucpr:0.797911\n","[8]\tvalidation_0-aucpr:0.792948\n","[9]\tvalidation_0-aucpr:0.796726\n","[10]\tvalidation_0-aucpr:0.780613\n","[11]\tvalidation_0-aucpr:0.777113\n","[12]\tvalidation_0-aucpr:0.777025\n","[13]\tvalidation_0-aucpr:0.776372\n","[14]\tvalidation_0-aucpr:0.799057\n","[15]\tvalidation_0-aucpr:0.798204\n","[16]\tvalidation_0-aucpr:0.807923\n","[17]\tvalidation_0-aucpr:0.805678\n","[18]\tvalidation_0-aucpr:0.807265\n","[19]\tvalidation_0-aucpr:0.819782\n","[20]\tvalidation_0-aucpr:0.818286\n","[21]\tvalidation_0-aucpr:0.8222\n","[22]\tvalidation_0-aucpr:0.824462\n","[23]\tvalidation_0-aucpr:0.831983\n","[24]\tvalidation_0-aucpr:0.830162\n","[25]\tvalidation_0-aucpr:0.831959\n","[26]\tvalidation_0-aucpr:0.850622\n","[27]\tvalidation_0-aucpr:0.847259\n","[28]\tvalidation_0-aucpr:0.855766\n","[29]\tvalidation_0-aucpr:0.855361\n","[30]\tvalidation_0-aucpr:0.858894\n","[31]\tvalidation_0-aucpr:0.862499\n","[32]\tvalidation_0-aucpr:0.859494\n","[33]\tvalidation_0-aucpr:0.864525\n","[34]\tvalidation_0-aucpr:0.867336\n","[35]\tvalidation_0-aucpr:0.870952\n","[36]\tvalidation_0-aucpr:0.870547\n","[37]\tvalidation_0-aucpr:0.868917\n","[38]\tvalidation_0-aucpr:0.870717\n","[39]\tvalidation_0-aucpr:0.870675\n","[40]\tvalidation_0-aucpr:0.870086\n","[41]\tvalidation_0-aucpr:0.869741\n","[42]\tvalidation_0-aucpr:0.869992\n","[43]\tvalidation_0-aucpr:0.87432\n","[44]\tvalidation_0-aucpr:0.8747\n","[45]\tvalidation_0-aucpr:0.873576\n","[46]\tvalidation_0-aucpr:0.875808\n","[47]\tvalidation_0-aucpr:0.88144\n","[48]\tvalidation_0-aucpr:0.885447\n","[49]\tvalidation_0-aucpr:0.8878\n","[50]\tvalidation_0-aucpr:0.889328\n","[51]\tvalidation_0-aucpr:0.892383\n","[52]\tvalidation_0-aucpr:0.896605\n","[53]\tvalidation_0-aucpr:0.896742\n","[54]\tvalidation_0-aucpr:0.901434\n","[55]\tvalidation_0-aucpr:0.904784\n","[56]\tvalidation_0-aucpr:0.911881\n","[57]\tvalidation_0-aucpr:0.914624\n","[58]\tvalidation_0-aucpr:0.920794\n","[59]\tvalidation_0-aucpr:0.920682\n","[60]\tvalidation_0-aucpr:0.922176\n","[61]\tvalidation_0-aucpr:0.923514\n","[62]\tvalidation_0-aucpr:0.92439\n","[63]\tvalidation_0-aucpr:0.925179\n","[64]\tvalidation_0-aucpr:0.926569\n","[65]\tvalidation_0-aucpr:0.929963\n","[66]\tvalidation_0-aucpr:0.93043\n","[67]\tvalidation_0-aucpr:0.930344\n","[68]\tvalidation_0-aucpr:0.932437\n","[69]\tvalidation_0-aucpr:0.93208\n","[70]\tvalidation_0-aucpr:0.932459\n","[71]\tvalidation_0-aucpr:0.93301\n","[72]\tvalidation_0-aucpr:0.933331\n","[73]\tvalidation_0-aucpr:0.935271\n","[74]\tvalidation_0-aucpr:0.938067\n","[75]\tvalidation_0-aucpr:0.938404\n","[76]\tvalidation_0-aucpr:0.9398\n","[77]\tvalidation_0-aucpr:0.941106\n","[78]\tvalidation_0-aucpr:0.939167\n","[79]\tvalidation_0-aucpr:0.940331\n","[80]\tvalidation_0-aucpr:0.940466\n","[81]\tvalidation_0-aucpr:0.942126\n","[82]\tvalidation_0-aucpr:0.943492\n","[83]\tvalidation_0-aucpr:0.943601\n","[84]\tvalidation_0-aucpr:0.945859\n","[85]\tvalidation_0-aucpr:0.945157\n","[86]\tvalidation_0-aucpr:0.944629\n","[87]\tvalidation_0-aucpr:0.946447\n","[88]\tvalidation_0-aucpr:0.945863\n","[89]\tvalidation_0-aucpr:0.947063\n","[90]\tvalidation_0-aucpr:0.947532\n","[91]\tvalidation_0-aucpr:0.947619\n","[92]\tvalidation_0-aucpr:0.947254\n","[93]\tvalidation_0-aucpr:0.947174\n","[94]\tvalidation_0-aucpr:0.948634\n","[95]\tvalidation_0-aucpr:0.949314\n","[96]\tvalidation_0-aucpr:0.947913\n","[97]\tvalidation_0-aucpr:0.949296\n","[98]\tvalidation_0-aucpr:0.948752\n","[99]\tvalidation_0-aucpr:0.949506\n","[100]\tvalidation_0-aucpr:0.949344\n","[101]\tvalidation_0-aucpr:0.950548\n","[102]\tvalidation_0-aucpr:0.950794\n","[103]\tvalidation_0-aucpr:0.950395\n","[104]\tvalidation_0-aucpr:0.950218\n","[105]\tvalidation_0-aucpr:0.95032\n","[106]\tvalidation_0-aucpr:0.951541\n","[107]\tvalidation_0-aucpr:0.951547\n","[108]\tvalidation_0-aucpr:0.952462\n","[109]\tvalidation_0-aucpr:0.953077\n","[110]\tvalidation_0-aucpr:0.953\n","[111]\tvalidation_0-aucpr:0.95415\n","[112]\tvalidation_0-aucpr:0.95472\n","[113]\tvalidation_0-aucpr:0.954491\n","[114]\tvalidation_0-aucpr:0.95422\n","[115]\tvalidation_0-aucpr:0.955378\n","[116]\tvalidation_0-aucpr:0.954519\n","[117]\tvalidation_0-aucpr:0.954131\n","[118]\tvalidation_0-aucpr:0.953863\n","[119]\tvalidation_0-aucpr:0.954306\n","[120]\tvalidation_0-aucpr:0.955871\n","[121]\tvalidation_0-aucpr:0.955698\n","[122]\tvalidation_0-aucpr:0.956333\n","[123]\tvalidation_0-aucpr:0.955218\n","[124]\tvalidation_0-aucpr:0.956772\n","[125]\tvalidation_0-aucpr:0.956159\n","[126]\tvalidation_0-aucpr:0.955974\n","[127]\tvalidation_0-aucpr:0.956411\n","[128]\tvalidation_0-aucpr:0.95612\n","[129]\tvalidation_0-aucpr:0.956829\n","[130]\tvalidation_0-aucpr:0.957417\n","[131]\tvalidation_0-aucpr:0.956435\n","[132]\tvalidation_0-aucpr:0.956342\n","[133]\tvalidation_0-aucpr:0.957537\n","[134]\tvalidation_0-aucpr:0.957212\n","[135]\tvalidation_0-aucpr:0.957695\n","[136]\tvalidation_0-aucpr:0.957949\n","[137]\tvalidation_0-aucpr:0.957814\n","[138]\tvalidation_0-aucpr:0.957689\n","[139]\tvalidation_0-aucpr:0.957791\n","[140]\tvalidation_0-aucpr:0.957807\n","[141]\tvalidation_0-aucpr:0.958233\n","[142]\tvalidation_0-aucpr:0.960226\n","[143]\tvalidation_0-aucpr:0.96016\n","[144]\tvalidation_0-aucpr:0.960803\n","[145]\tvalidation_0-aucpr:0.960591\n","[146]\tvalidation_0-aucpr:0.961473\n","[147]\tvalidation_0-aucpr:0.96054\n","[148]\tvalidation_0-aucpr:0.961322\n","[149]\tvalidation_0-aucpr:0.961058\n","[150]\tvalidation_0-aucpr:0.961341\n","[151]\tvalidation_0-aucpr:0.961305\n","[152]\tvalidation_0-aucpr:0.961646\n","[153]\tvalidation_0-aucpr:0.961485\n","[154]\tvalidation_0-aucpr:0.961631\n","[155]\tvalidation_0-aucpr:0.96139\n","[156]\tvalidation_0-aucpr:0.961222\n","[157]\tvalidation_0-aucpr:0.960553\n","[158]\tvalidation_0-aucpr:0.960553\n","[159]\tvalidation_0-aucpr:0.961061\n","[160]\tvalidation_0-aucpr:0.96113\n","Stopping. Best iteration:\n","[152]\tvalidation_0-aucpr:0.961646\n","\n","\n","Done with week 32\n","Starting week 33\n","\n","[0]\tvalidation_0-aucpr:0.776748\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.756597\n","[2]\tvalidation_0-aucpr:0.780409\n","[3]\tvalidation_0-aucpr:0.788941\n","[4]\tvalidation_0-aucpr:0.7882\n","[5]\tvalidation_0-aucpr:0.7914\n","[6]\tvalidation_0-aucpr:0.797954\n","[7]\tvalidation_0-aucpr:0.786142\n","[8]\tvalidation_0-aucpr:0.786059\n","[9]\tvalidation_0-aucpr:0.776976\n","[10]\tvalidation_0-aucpr:0.772844\n","[11]\tvalidation_0-aucpr:0.769311\n","[12]\tvalidation_0-aucpr:0.765627\n","[13]\tvalidation_0-aucpr:0.762376\n","[14]\tvalidation_0-aucpr:0.76231\n","Stopping. Best iteration:\n","[6]\tvalidation_0-aucpr:0.797954\n","\n","\n","Done with week 33\n","Starting week 34\n","\n","[0]\tvalidation_0-aucpr:0.84954\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.852621\n","[2]\tvalidation_0-aucpr:0.872963\n","[3]\tvalidation_0-aucpr:0.870187\n","[4]\tvalidation_0-aucpr:0.854826\n","[5]\tvalidation_0-aucpr:0.846799\n","[6]\tvalidation_0-aucpr:0.846063\n","[7]\tvalidation_0-aucpr:0.846096\n","[8]\tvalidation_0-aucpr:0.853777\n","[9]\tvalidation_0-aucpr:0.852083\n","[10]\tvalidation_0-aucpr:0.853551\n","Stopping. Best iteration:\n","[2]\tvalidation_0-aucpr:0.872963\n","\n","\n","Done with week 34\n","Starting week 35\n","\n","[0]\tvalidation_0-aucpr:0.830552\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.830821\n","[2]\tvalidation_0-aucpr:0.866579\n","[3]\tvalidation_0-aucpr:0.855366\n","[4]\tvalidation_0-aucpr:0.870108\n","[5]\tvalidation_0-aucpr:0.871689\n","[6]\tvalidation_0-aucpr:0.875361\n","[7]\tvalidation_0-aucpr:0.884601\n","[8]\tvalidation_0-aucpr:0.883527\n","[9]\tvalidation_0-aucpr:0.88438\n","[10]\tvalidation_0-aucpr:0.881799\n","[11]\tvalidation_0-aucpr:0.880414\n","[12]\tvalidation_0-aucpr:0.869276\n","[13]\tvalidation_0-aucpr:0.871887\n","[14]\tvalidation_0-aucpr:0.871063\n","[15]\tvalidation_0-aucpr:0.876102\n","Stopping. Best iteration:\n","[7]\tvalidation_0-aucpr:0.884601\n","\n","\n","Done with week 35\n","Starting week 36\n","\n","[0]\tvalidation_0-aucpr:0.889784\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.895802\n","[2]\tvalidation_0-aucpr:0.898575\n","[3]\tvalidation_0-aucpr:0.903285\n","[4]\tvalidation_0-aucpr:0.908154\n","[5]\tvalidation_0-aucpr:0.906858\n","[6]\tvalidation_0-aucpr:0.902328\n","[7]\tvalidation_0-aucpr:0.903932\n","[8]\tvalidation_0-aucpr:0.904411\n","[9]\tvalidation_0-aucpr:0.908094\n","[10]\tvalidation_0-aucpr:0.91009\n","[11]\tvalidation_0-aucpr:0.909377\n","[12]\tvalidation_0-aucpr:0.907582\n","[13]\tvalidation_0-aucpr:0.910604\n","[14]\tvalidation_0-aucpr:0.908573\n","[15]\tvalidation_0-aucpr:0.90668\n","[16]\tvalidation_0-aucpr:0.911037\n","[17]\tvalidation_0-aucpr:0.908015\n","[18]\tvalidation_0-aucpr:0.914425\n","[19]\tvalidation_0-aucpr:0.914492\n","[20]\tvalidation_0-aucpr:0.912771\n","[21]\tvalidation_0-aucpr:0.914076\n","[22]\tvalidation_0-aucpr:0.914966\n","[23]\tvalidation_0-aucpr:0.913247\n","[24]\tvalidation_0-aucpr:0.913383\n","[25]\tvalidation_0-aucpr:0.91134\n","[26]\tvalidation_0-aucpr:0.905756\n","[27]\tvalidation_0-aucpr:0.905534\n","[28]\tvalidation_0-aucpr:0.906629\n","[29]\tvalidation_0-aucpr:0.904579\n","[30]\tvalidation_0-aucpr:0.905352\n","Stopping. Best iteration:\n","[22]\tvalidation_0-aucpr:0.914966\n","\n","\n","Done with week 36\n","Starting week 37\n","\n","[0]\tvalidation_0-aucpr:0.870165\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.879662\n","[2]\tvalidation_0-aucpr:0.879397\n","[3]\tvalidation_0-aucpr:0.888567\n","[4]\tvalidation_0-aucpr:0.866927\n","[5]\tvalidation_0-aucpr:0.881494\n","[6]\tvalidation_0-aucpr:0.883166\n","[7]\tvalidation_0-aucpr:0.885698\n","[8]\tvalidation_0-aucpr:0.884806\n","[9]\tvalidation_0-aucpr:0.884228\n","[10]\tvalidation_0-aucpr:0.885381\n","[11]\tvalidation_0-aucpr:0.88982\n","[12]\tvalidation_0-aucpr:0.889638\n","[13]\tvalidation_0-aucpr:0.886169\n","[14]\tvalidation_0-aucpr:0.888649\n","[15]\tvalidation_0-aucpr:0.894906\n","[16]\tvalidation_0-aucpr:0.899172\n","[17]\tvalidation_0-aucpr:0.90213\n","[18]\tvalidation_0-aucpr:0.905302\n","[19]\tvalidation_0-aucpr:0.895341\n","[20]\tvalidation_0-aucpr:0.903832\n","[21]\tvalidation_0-aucpr:0.902404\n","[22]\tvalidation_0-aucpr:0.903656\n","[23]\tvalidation_0-aucpr:0.909915\n","[24]\tvalidation_0-aucpr:0.906652\n","[25]\tvalidation_0-aucpr:0.907844\n","[26]\tvalidation_0-aucpr:0.906241\n","[27]\tvalidation_0-aucpr:0.903421\n","[28]\tvalidation_0-aucpr:0.909194\n","[29]\tvalidation_0-aucpr:0.909246\n","[30]\tvalidation_0-aucpr:0.917686\n","[31]\tvalidation_0-aucpr:0.914279\n","[32]\tvalidation_0-aucpr:0.910494\n","[33]\tvalidation_0-aucpr:0.912454\n","[34]\tvalidation_0-aucpr:0.909297\n","[35]\tvalidation_0-aucpr:0.90641\n","[36]\tvalidation_0-aucpr:0.908834\n","[37]\tvalidation_0-aucpr:0.90836\n","[38]\tvalidation_0-aucpr:0.911622\n","Stopping. Best iteration:\n","[30]\tvalidation_0-aucpr:0.917686\n","\n","\n","Done with week 37\n","Starting week 38\n","\n","[0]\tvalidation_0-aucpr:0.864467\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.889125\n","[2]\tvalidation_0-aucpr:0.892183\n","[3]\tvalidation_0-aucpr:0.892754\n","[4]\tvalidation_0-aucpr:0.932111\n","[5]\tvalidation_0-aucpr:0.931236\n","[6]\tvalidation_0-aucpr:0.92476\n","[7]\tvalidation_0-aucpr:0.92919\n","[8]\tvalidation_0-aucpr:0.930378\n","[9]\tvalidation_0-aucpr:0.945818\n","[10]\tvalidation_0-aucpr:0.951063\n","[11]\tvalidation_0-aucpr:0.950534\n","[12]\tvalidation_0-aucpr:0.945606\n","[13]\tvalidation_0-aucpr:0.945853\n","[14]\tvalidation_0-aucpr:0.944014\n","[15]\tvalidation_0-aucpr:0.940318\n","[16]\tvalidation_0-aucpr:0.941594\n","[17]\tvalidation_0-aucpr:0.933325\n","[18]\tvalidation_0-aucpr:0.932273\n","Stopping. Best iteration:\n","[10]\tvalidation_0-aucpr:0.951063\n","\n","\n","Done with week 38\n","Starting week 39\n","\n","[0]\tvalidation_0-aucpr:0.868029\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.874505\n","[2]\tvalidation_0-aucpr:0.886913\n","[3]\tvalidation_0-aucpr:0.870625\n","[4]\tvalidation_0-aucpr:0.872696\n","[5]\tvalidation_0-aucpr:0.880644\n","[6]\tvalidation_0-aucpr:0.876681\n","[7]\tvalidation_0-aucpr:0.878018\n","[8]\tvalidation_0-aucpr:0.89455\n","[9]\tvalidation_0-aucpr:0.893702\n","[10]\tvalidation_0-aucpr:0.897537\n","[11]\tvalidation_0-aucpr:0.896582\n","[12]\tvalidation_0-aucpr:0.895338\n","[13]\tvalidation_0-aucpr:0.893836\n","[14]\tvalidation_0-aucpr:0.91223\n","[15]\tvalidation_0-aucpr:0.911578\n","[16]\tvalidation_0-aucpr:0.91149\n","[17]\tvalidation_0-aucpr:0.916573\n","[18]\tvalidation_0-aucpr:0.915013\n","[19]\tvalidation_0-aucpr:0.91924\n","[20]\tvalidation_0-aucpr:0.918211\n","[21]\tvalidation_0-aucpr:0.918091\n","[22]\tvalidation_0-aucpr:0.923396\n","[23]\tvalidation_0-aucpr:0.921755\n","[24]\tvalidation_0-aucpr:0.918198\n","[25]\tvalidation_0-aucpr:0.915256\n","[26]\tvalidation_0-aucpr:0.919482\n","[27]\tvalidation_0-aucpr:0.919619\n","[28]\tvalidation_0-aucpr:0.919298\n","[29]\tvalidation_0-aucpr:0.919323\n","[30]\tvalidation_0-aucpr:0.919717\n","Stopping. Best iteration:\n","[22]\tvalidation_0-aucpr:0.923396\n","\n","\n","Done with week 39\n","Starting week 40\n","\n","[0]\tvalidation_0-aucpr:0.845608\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.865294\n","[2]\tvalidation_0-aucpr:0.86371\n","[3]\tvalidation_0-aucpr:0.85994\n","[4]\tvalidation_0-aucpr:0.861441\n","[5]\tvalidation_0-aucpr:0.867194\n","[6]\tvalidation_0-aucpr:0.86903\n","[7]\tvalidation_0-aucpr:0.864336\n","[8]\tvalidation_0-aucpr:0.863681\n","[9]\tvalidation_0-aucpr:0.863909\n","[10]\tvalidation_0-aucpr:0.867148\n","[11]\tvalidation_0-aucpr:0.86641\n","[12]\tvalidation_0-aucpr:0.865838\n","[13]\tvalidation_0-aucpr:0.871809\n","[14]\tvalidation_0-aucpr:0.863396\n","[15]\tvalidation_0-aucpr:0.870165\n","[16]\tvalidation_0-aucpr:0.884267\n","[17]\tvalidation_0-aucpr:0.884496\n","[18]\tvalidation_0-aucpr:0.885628\n","[19]\tvalidation_0-aucpr:0.883664\n","[20]\tvalidation_0-aucpr:0.885089\n","[21]\tvalidation_0-aucpr:0.890025\n","[22]\tvalidation_0-aucpr:0.894069\n","[23]\tvalidation_0-aucpr:0.883773\n","[24]\tvalidation_0-aucpr:0.888032\n","[25]\tvalidation_0-aucpr:0.895451\n","[26]\tvalidation_0-aucpr:0.894979\n","[27]\tvalidation_0-aucpr:0.894283\n","[28]\tvalidation_0-aucpr:0.896467\n","[29]\tvalidation_0-aucpr:0.896479\n","[30]\tvalidation_0-aucpr:0.898623\n","[31]\tvalidation_0-aucpr:0.890219\n","[32]\tvalidation_0-aucpr:0.890186\n","[33]\tvalidation_0-aucpr:0.897879\n","[34]\tvalidation_0-aucpr:0.893867\n","[35]\tvalidation_0-aucpr:0.891025\n","[36]\tvalidation_0-aucpr:0.886027\n","[37]\tvalidation_0-aucpr:0.890015\n","[38]\tvalidation_0-aucpr:0.889656\n","Stopping. Best iteration:\n","[30]\tvalidation_0-aucpr:0.898623\n","\n","\n","Done with week 40\n","Starting week 41\n","\n","[0]\tvalidation_0-aucpr:0.868964\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.873429\n","[2]\tvalidation_0-aucpr:0.849783\n","[3]\tvalidation_0-aucpr:0.854402\n","[4]\tvalidation_0-aucpr:0.852926\n","[5]\tvalidation_0-aucpr:0.853703\n","[6]\tvalidation_0-aucpr:0.849582\n","[7]\tvalidation_0-aucpr:0.853584\n","[8]\tvalidation_0-aucpr:0.843078\n","[9]\tvalidation_0-aucpr:0.84469\n","Stopping. Best iteration:\n","[1]\tvalidation_0-aucpr:0.873429\n","\n","\n","Done with week 41\n","Starting week 42\n","\n","[0]\tvalidation_0-aucpr:0.878846\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.897901\n","[2]\tvalidation_0-aucpr:0.895643\n","[3]\tvalidation_0-aucpr:0.89525\n","[4]\tvalidation_0-aucpr:0.899743\n","[5]\tvalidation_0-aucpr:0.889241\n","[6]\tvalidation_0-aucpr:0.896335\n","[7]\tvalidation_0-aucpr:0.910673\n","[8]\tvalidation_0-aucpr:0.903617\n","[9]\tvalidation_0-aucpr:0.904905\n","[10]\tvalidation_0-aucpr:0.902234\n","[11]\tvalidation_0-aucpr:0.905297\n","[12]\tvalidation_0-aucpr:0.908695\n","[13]\tvalidation_0-aucpr:0.907868\n","[14]\tvalidation_0-aucpr:0.914187\n","[15]\tvalidation_0-aucpr:0.911253\n","[16]\tvalidation_0-aucpr:0.912042\n","[17]\tvalidation_0-aucpr:0.920384\n","[18]\tvalidation_0-aucpr:0.919988\n","[19]\tvalidation_0-aucpr:0.930578\n","[20]\tvalidation_0-aucpr:0.925658\n","[21]\tvalidation_0-aucpr:0.923366\n","[22]\tvalidation_0-aucpr:0.924024\n","[23]\tvalidation_0-aucpr:0.927727\n","[24]\tvalidation_0-aucpr:0.921926\n","[25]\tvalidation_0-aucpr:0.923132\n","[26]\tvalidation_0-aucpr:0.923456\n","[27]\tvalidation_0-aucpr:0.923672\n","Stopping. Best iteration:\n","[19]\tvalidation_0-aucpr:0.930578\n","\n","\n","Done with week 42\n","Starting week 43\n","\n","[0]\tvalidation_0-aucpr:0.841733\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.84681\n","[2]\tvalidation_0-aucpr:0.884287\n","[3]\tvalidation_0-aucpr:0.881353\n","[4]\tvalidation_0-aucpr:0.881585\n","[5]\tvalidation_0-aucpr:0.88992\n","[6]\tvalidation_0-aucpr:0.883861\n","[7]\tvalidation_0-aucpr:0.88304\n","[8]\tvalidation_0-aucpr:0.897777\n","[9]\tvalidation_0-aucpr:0.898195\n","[10]\tvalidation_0-aucpr:0.898323\n","[11]\tvalidation_0-aucpr:0.905724\n","[12]\tvalidation_0-aucpr:0.90703\n","[13]\tvalidation_0-aucpr:0.9078\n","[14]\tvalidation_0-aucpr:0.908386\n","[15]\tvalidation_0-aucpr:0.909586\n","[16]\tvalidation_0-aucpr:0.91157\n","[17]\tvalidation_0-aucpr:0.910889\n","[18]\tvalidation_0-aucpr:0.910842\n","[19]\tvalidation_0-aucpr:0.924126\n","[20]\tvalidation_0-aucpr:0.930317\n","[21]\tvalidation_0-aucpr:0.9321\n","[22]\tvalidation_0-aucpr:0.932435\n","[23]\tvalidation_0-aucpr:0.931607\n","[24]\tvalidation_0-aucpr:0.932931\n","[25]\tvalidation_0-aucpr:0.928248\n","[26]\tvalidation_0-aucpr:0.930253\n","[27]\tvalidation_0-aucpr:0.930978\n","[28]\tvalidation_0-aucpr:0.926288\n","[29]\tvalidation_0-aucpr:0.927845\n","[30]\tvalidation_0-aucpr:0.927815\n","[31]\tvalidation_0-aucpr:0.929544\n","[32]\tvalidation_0-aucpr:0.932037\n","Stopping. Best iteration:\n","[24]\tvalidation_0-aucpr:0.932931\n","\n","\n","Done with week 43\n","Starting week 44\n","\n","[0]\tvalidation_0-aucpr:0.854226\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.85295\n","[2]\tvalidation_0-aucpr:0.860417\n","[3]\tvalidation_0-aucpr:0.865676\n","[4]\tvalidation_0-aucpr:0.867872\n","[5]\tvalidation_0-aucpr:0.870076\n","[6]\tvalidation_0-aucpr:0.875232\n","[7]\tvalidation_0-aucpr:0.883709\n","[8]\tvalidation_0-aucpr:0.880004\n","[9]\tvalidation_0-aucpr:0.890608\n","[10]\tvalidation_0-aucpr:0.888935\n","[11]\tvalidation_0-aucpr:0.897832\n","[12]\tvalidation_0-aucpr:0.89538\n","[13]\tvalidation_0-aucpr:0.894956\n","[14]\tvalidation_0-aucpr:0.896069\n","[15]\tvalidation_0-aucpr:0.897012\n","[16]\tvalidation_0-aucpr:0.903326\n","[17]\tvalidation_0-aucpr:0.90245\n","[18]\tvalidation_0-aucpr:0.91392\n","[19]\tvalidation_0-aucpr:0.906828\n","[20]\tvalidation_0-aucpr:0.910012\n","[21]\tvalidation_0-aucpr:0.911539\n","[22]\tvalidation_0-aucpr:0.913572\n","[23]\tvalidation_0-aucpr:0.915829\n","[24]\tvalidation_0-aucpr:0.923622\n","[25]\tvalidation_0-aucpr:0.921033\n","[26]\tvalidation_0-aucpr:0.923084\n","[27]\tvalidation_0-aucpr:0.921261\n","[28]\tvalidation_0-aucpr:0.92651\n","[29]\tvalidation_0-aucpr:0.929026\n","[30]\tvalidation_0-aucpr:0.930682\n","[31]\tvalidation_0-aucpr:0.932742\n","[32]\tvalidation_0-aucpr:0.937789\n","[33]\tvalidation_0-aucpr:0.940604\n","[34]\tvalidation_0-aucpr:0.936756\n","[35]\tvalidation_0-aucpr:0.936862\n","[36]\tvalidation_0-aucpr:0.936408\n","[37]\tvalidation_0-aucpr:0.936778\n","[38]\tvalidation_0-aucpr:0.937622\n","[39]\tvalidation_0-aucpr:0.939857\n","[40]\tvalidation_0-aucpr:0.945446\n","[41]\tvalidation_0-aucpr:0.949003\n","[42]\tvalidation_0-aucpr:0.956977\n","[43]\tvalidation_0-aucpr:0.960187\n","[44]\tvalidation_0-aucpr:0.963955\n","[45]\tvalidation_0-aucpr:0.964904\n","[46]\tvalidation_0-aucpr:0.967844\n","[47]\tvalidation_0-aucpr:0.972098\n","[48]\tvalidation_0-aucpr:0.972254\n","[49]\tvalidation_0-aucpr:0.974751\n","[50]\tvalidation_0-aucpr:0.976346\n","[51]\tvalidation_0-aucpr:0.977413\n","[52]\tvalidation_0-aucpr:0.978862\n","[53]\tvalidation_0-aucpr:0.978247\n","[54]\tvalidation_0-aucpr:0.979093\n","[55]\tvalidation_0-aucpr:0.979977\n","[56]\tvalidation_0-aucpr:0.98024\n","[57]\tvalidation_0-aucpr:0.982009\n","[58]\tvalidation_0-aucpr:0.982781\n","[59]\tvalidation_0-aucpr:0.98377\n","[60]\tvalidation_0-aucpr:0.984061\n","[61]\tvalidation_0-aucpr:0.984501\n","[62]\tvalidation_0-aucpr:0.985503\n","[63]\tvalidation_0-aucpr:0.985777\n","[64]\tvalidation_0-aucpr:0.985828\n","[65]\tvalidation_0-aucpr:0.986577\n","[66]\tvalidation_0-aucpr:0.98688\n","[67]\tvalidation_0-aucpr:0.987211\n","[68]\tvalidation_0-aucpr:0.987739\n","[69]\tvalidation_0-aucpr:0.988495\n","[70]\tvalidation_0-aucpr:0.988726\n","[71]\tvalidation_0-aucpr:0.988991\n","[72]\tvalidation_0-aucpr:0.989406\n","[73]\tvalidation_0-aucpr:0.989496\n","[74]\tvalidation_0-aucpr:0.990144\n","[75]\tvalidation_0-aucpr:0.990349\n","[76]\tvalidation_0-aucpr:0.990471\n","[77]\tvalidation_0-aucpr:0.990581\n","[78]\tvalidation_0-aucpr:0.990593\n","[79]\tvalidation_0-aucpr:0.990778\n","[80]\tvalidation_0-aucpr:0.991185\n","[81]\tvalidation_0-aucpr:0.991064\n","[82]\tvalidation_0-aucpr:0.99098\n","[83]\tvalidation_0-aucpr:0.991444\n","[84]\tvalidation_0-aucpr:0.991475\n","[85]\tvalidation_0-aucpr:0.991482\n","[86]\tvalidation_0-aucpr:0.991724\n","[87]\tvalidation_0-aucpr:0.991645\n","[88]\tvalidation_0-aucpr:0.991084\n","[89]\tvalidation_0-aucpr:0.991408\n","[90]\tvalidation_0-aucpr:0.991258\n","[91]\tvalidation_0-aucpr:0.991697\n","[92]\tvalidation_0-aucpr:0.991725\n","[93]\tvalidation_0-aucpr:0.991642\n","[94]\tvalidation_0-aucpr:0.99177\n","[95]\tvalidation_0-aucpr:0.991776\n","[96]\tvalidation_0-aucpr:0.991809\n","[97]\tvalidation_0-aucpr:0.991796\n","[98]\tvalidation_0-aucpr:0.991701\n","[99]\tvalidation_0-aucpr:0.991779\n","[100]\tvalidation_0-aucpr:0.991355\n","[101]\tvalidation_0-aucpr:0.991405\n","[102]\tvalidation_0-aucpr:0.991069\n","[103]\tvalidation_0-aucpr:0.991289\n","[104]\tvalidation_0-aucpr:0.991358\n","Stopping. Best iteration:\n","[96]\tvalidation_0-aucpr:0.991809\n","\n","\n","Done with week 44\n","Starting week 45\n","\n","[0]\tvalidation_0-aucpr:0.87519\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.872738\n","[2]\tvalidation_0-aucpr:0.875225\n","[3]\tvalidation_0-aucpr:0.874508\n","[4]\tvalidation_0-aucpr:0.87347\n","[5]\tvalidation_0-aucpr:0.873349\n","[6]\tvalidation_0-aucpr:0.877034\n","[7]\tvalidation_0-aucpr:0.87594\n","[8]\tvalidation_0-aucpr:0.880842\n","[9]\tvalidation_0-aucpr:0.87253\n","[10]\tvalidation_0-aucpr:0.869851\n","[11]\tvalidation_0-aucpr:0.878239\n","[12]\tvalidation_0-aucpr:0.89019\n","[13]\tvalidation_0-aucpr:0.900756\n","[14]\tvalidation_0-aucpr:0.906348\n","[15]\tvalidation_0-aucpr:0.916393\n","[16]\tvalidation_0-aucpr:0.915224\n","[17]\tvalidation_0-aucpr:0.914301\n","[18]\tvalidation_0-aucpr:0.916778\n","[19]\tvalidation_0-aucpr:0.915974\n","[20]\tvalidation_0-aucpr:0.920286\n","[21]\tvalidation_0-aucpr:0.923376\n","[22]\tvalidation_0-aucpr:0.926002\n","[23]\tvalidation_0-aucpr:0.929153\n","[24]\tvalidation_0-aucpr:0.923469\n","[25]\tvalidation_0-aucpr:0.932441\n","[26]\tvalidation_0-aucpr:0.933518\n","[27]\tvalidation_0-aucpr:0.936525\n","[28]\tvalidation_0-aucpr:0.941464\n","[29]\tvalidation_0-aucpr:0.940078\n","[30]\tvalidation_0-aucpr:0.94045\n","[31]\tvalidation_0-aucpr:0.942535\n","[32]\tvalidation_0-aucpr:0.941253\n","[33]\tvalidation_0-aucpr:0.942501\n","[34]\tvalidation_0-aucpr:0.943063\n","[35]\tvalidation_0-aucpr:0.941966\n","[36]\tvalidation_0-aucpr:0.943717\n","[37]\tvalidation_0-aucpr:0.942177\n","[38]\tvalidation_0-aucpr:0.943713\n","[39]\tvalidation_0-aucpr:0.945961\n","[40]\tvalidation_0-aucpr:0.94759\n","[41]\tvalidation_0-aucpr:0.947418\n","[42]\tvalidation_0-aucpr:0.948039\n","[43]\tvalidation_0-aucpr:0.947049\n","[44]\tvalidation_0-aucpr:0.946183\n","[45]\tvalidation_0-aucpr:0.946709\n","[46]\tvalidation_0-aucpr:0.95024\n","[47]\tvalidation_0-aucpr:0.950016\n","[48]\tvalidation_0-aucpr:0.953185\n","[49]\tvalidation_0-aucpr:0.960688\n","[50]\tvalidation_0-aucpr:0.964189\n","[51]\tvalidation_0-aucpr:0.967357\n","[52]\tvalidation_0-aucpr:0.970599\n","[53]\tvalidation_0-aucpr:0.972614\n","[54]\tvalidation_0-aucpr:0.973101\n","[55]\tvalidation_0-aucpr:0.975427\n","[56]\tvalidation_0-aucpr:0.977697\n","[57]\tvalidation_0-aucpr:0.978158\n","[58]\tvalidation_0-aucpr:0.978997\n","[59]\tvalidation_0-aucpr:0.980695\n","[60]\tvalidation_0-aucpr:0.982319\n","[61]\tvalidation_0-aucpr:0.981552\n","[62]\tvalidation_0-aucpr:0.982111\n","[63]\tvalidation_0-aucpr:0.982253\n","[64]\tvalidation_0-aucpr:0.982339\n","[65]\tvalidation_0-aucpr:0.981919\n","[66]\tvalidation_0-aucpr:0.981165\n","[67]\tvalidation_0-aucpr:0.982627\n","[68]\tvalidation_0-aucpr:0.985027\n","[69]\tvalidation_0-aucpr:0.984258\n","[70]\tvalidation_0-aucpr:0.984722\n","[71]\tvalidation_0-aucpr:0.98509\n","[72]\tvalidation_0-aucpr:0.987005\n","[73]\tvalidation_0-aucpr:0.988311\n","[74]\tvalidation_0-aucpr:0.988627\n","[75]\tvalidation_0-aucpr:0.988775\n","[76]\tvalidation_0-aucpr:0.989076\n","[77]\tvalidation_0-aucpr:0.988714\n","[78]\tvalidation_0-aucpr:0.989266\n","[79]\tvalidation_0-aucpr:0.989879\n","[80]\tvalidation_0-aucpr:0.989817\n","[81]\tvalidation_0-aucpr:0.990634\n","[82]\tvalidation_0-aucpr:0.990526\n","[83]\tvalidation_0-aucpr:0.99013\n","[84]\tvalidation_0-aucpr:0.990108\n","[85]\tvalidation_0-aucpr:0.989745\n","[86]\tvalidation_0-aucpr:0.990391\n","[87]\tvalidation_0-aucpr:0.990465\n","[88]\tvalidation_0-aucpr:0.991127\n","[89]\tvalidation_0-aucpr:0.99137\n","[90]\tvalidation_0-aucpr:0.991365\n","[91]\tvalidation_0-aucpr:0.990912\n","[92]\tvalidation_0-aucpr:0.991141\n","[93]\tvalidation_0-aucpr:0.991529\n","[94]\tvalidation_0-aucpr:0.991035\n","[95]\tvalidation_0-aucpr:0.990887\n","[96]\tvalidation_0-aucpr:0.990739\n","[97]\tvalidation_0-aucpr:0.991601\n","[98]\tvalidation_0-aucpr:0.991475\n","[99]\tvalidation_0-aucpr:0.991641\n","[100]\tvalidation_0-aucpr:0.991818\n","[101]\tvalidation_0-aucpr:0.991742\n","[102]\tvalidation_0-aucpr:0.991804\n","[103]\tvalidation_0-aucpr:0.991448\n","[104]\tvalidation_0-aucpr:0.99126\n","[105]\tvalidation_0-aucpr:0.991544\n","[106]\tvalidation_0-aucpr:0.991985\n","[107]\tvalidation_0-aucpr:0.991972\n","[108]\tvalidation_0-aucpr:0.991988\n","[109]\tvalidation_0-aucpr:0.992072\n","[110]\tvalidation_0-aucpr:0.992231\n","[111]\tvalidation_0-aucpr:0.992148\n","[112]\tvalidation_0-aucpr:0.992292\n","[113]\tvalidation_0-aucpr:0.992159\n","[114]\tvalidation_0-aucpr:0.992281\n","[115]\tvalidation_0-aucpr:0.992498\n","[116]\tvalidation_0-aucpr:0.992907\n","[117]\tvalidation_0-aucpr:0.993135\n","[118]\tvalidation_0-aucpr:0.992914\n","[119]\tvalidation_0-aucpr:0.993286\n","[120]\tvalidation_0-aucpr:0.993233\n","[121]\tvalidation_0-aucpr:0.993205\n","[122]\tvalidation_0-aucpr:0.993223\n","[123]\tvalidation_0-aucpr:0.993279\n","[124]\tvalidation_0-aucpr:0.993277\n","[125]\tvalidation_0-aucpr:0.993328\n","[126]\tvalidation_0-aucpr:0.993702\n","[127]\tvalidation_0-aucpr:0.993702\n","[128]\tvalidation_0-aucpr:0.993809\n","[129]\tvalidation_0-aucpr:0.994308\n","[130]\tvalidation_0-aucpr:0.99421\n","[131]\tvalidation_0-aucpr:0.994135\n","[132]\tvalidation_0-aucpr:0.994043\n","[133]\tvalidation_0-aucpr:0.994199\n","[134]\tvalidation_0-aucpr:0.994263\n","[135]\tvalidation_0-aucpr:0.994324\n","[136]\tvalidation_0-aucpr:0.994345\n","[137]\tvalidation_0-aucpr:0.9945\n","[138]\tvalidation_0-aucpr:0.994462\n","[139]\tvalidation_0-aucpr:0.994533\n","[140]\tvalidation_0-aucpr:0.994474\n","[141]\tvalidation_0-aucpr:0.99435\n","[142]\tvalidation_0-aucpr:0.994769\n","[143]\tvalidation_0-aucpr:0.994819\n","[144]\tvalidation_0-aucpr:0.994839\n","[145]\tvalidation_0-aucpr:0.994798\n","[146]\tvalidation_0-aucpr:0.994959\n","[147]\tvalidation_0-aucpr:0.994489\n","[148]\tvalidation_0-aucpr:0.994513\n","[149]\tvalidation_0-aucpr:0.994744\n","[150]\tvalidation_0-aucpr:0.994571\n","[151]\tvalidation_0-aucpr:0.994609\n","[152]\tvalidation_0-aucpr:0.99466\n","[153]\tvalidation_0-aucpr:0.994609\n","[154]\tvalidation_0-aucpr:0.99479\n","Stopping. Best iteration:\n","[146]\tvalidation_0-aucpr:0.994959\n","\n","\n","Done with week 45\n","Starting week 46\n","\n","[0]\tvalidation_0-aucpr:0.819103\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.817327\n","[2]\tvalidation_0-aucpr:0.82871\n","[3]\tvalidation_0-aucpr:0.852392\n","[4]\tvalidation_0-aucpr:0.859967\n","[5]\tvalidation_0-aucpr:0.862269\n","[6]\tvalidation_0-aucpr:0.885082\n","[7]\tvalidation_0-aucpr:0.885731\n","[8]\tvalidation_0-aucpr:0.918582\n","[9]\tvalidation_0-aucpr:0.918239\n","[10]\tvalidation_0-aucpr:0.919371\n","[11]\tvalidation_0-aucpr:0.920096\n","[12]\tvalidation_0-aucpr:0.918708\n","[13]\tvalidation_0-aucpr:0.929516\n","[14]\tvalidation_0-aucpr:0.926085\n","[15]\tvalidation_0-aucpr:0.925783\n","[16]\tvalidation_0-aucpr:0.927052\n","[17]\tvalidation_0-aucpr:0.925431\n","[18]\tvalidation_0-aucpr:0.924371\n","[19]\tvalidation_0-aucpr:0.924517\n","[20]\tvalidation_0-aucpr:0.929068\n","[21]\tvalidation_0-aucpr:0.927895\n","Stopping. Best iteration:\n","[13]\tvalidation_0-aucpr:0.929516\n","\n","\n","Done with week 46\n","Starting week 47\n","\n","[0]\tvalidation_0-aucpr:0.812029\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.816513\n","[2]\tvalidation_0-aucpr:0.823276\n","[3]\tvalidation_0-aucpr:0.819321\n","[4]\tvalidation_0-aucpr:0.827049\n","[5]\tvalidation_0-aucpr:0.832809\n","[6]\tvalidation_0-aucpr:0.833007\n","[7]\tvalidation_0-aucpr:0.833619\n","[8]\tvalidation_0-aucpr:0.832024\n","[9]\tvalidation_0-aucpr:0.829333\n","[10]\tvalidation_0-aucpr:0.830858\n","[11]\tvalidation_0-aucpr:0.831757\n","[12]\tvalidation_0-aucpr:0.830815\n","[13]\tvalidation_0-aucpr:0.830315\n","[14]\tvalidation_0-aucpr:0.832192\n","[15]\tvalidation_0-aucpr:0.834243\n","[16]\tvalidation_0-aucpr:0.85394\n","[17]\tvalidation_0-aucpr:0.862246\n","[18]\tvalidation_0-aucpr:0.870672\n","[19]\tvalidation_0-aucpr:0.867662\n","[20]\tvalidation_0-aucpr:0.880124\n","[21]\tvalidation_0-aucpr:0.879769\n","[22]\tvalidation_0-aucpr:0.883935\n","[23]\tvalidation_0-aucpr:0.877474\n","[24]\tvalidation_0-aucpr:0.883357\n","[25]\tvalidation_0-aucpr:0.890529\n","[26]\tvalidation_0-aucpr:0.889338\n","[27]\tvalidation_0-aucpr:0.890581\n","[28]\tvalidation_0-aucpr:0.892775\n","[29]\tvalidation_0-aucpr:0.895828\n","[30]\tvalidation_0-aucpr:0.898555\n","[31]\tvalidation_0-aucpr:0.902062\n","[32]\tvalidation_0-aucpr:0.902131\n","[33]\tvalidation_0-aucpr:0.902051\n","[34]\tvalidation_0-aucpr:0.90287\n","[35]\tvalidation_0-aucpr:0.905751\n","[36]\tvalidation_0-aucpr:0.909323\n","[37]\tvalidation_0-aucpr:0.912242\n","[38]\tvalidation_0-aucpr:0.912163\n","[39]\tvalidation_0-aucpr:0.913668\n","[40]\tvalidation_0-aucpr:0.915374\n","[41]\tvalidation_0-aucpr:0.91283\n","[42]\tvalidation_0-aucpr:0.917071\n","[43]\tvalidation_0-aucpr:0.915748\n","[44]\tvalidation_0-aucpr:0.916326\n","[45]\tvalidation_0-aucpr:0.918701\n","[46]\tvalidation_0-aucpr:0.914613\n","[47]\tvalidation_0-aucpr:0.913874\n","[48]\tvalidation_0-aucpr:0.915751\n","[49]\tvalidation_0-aucpr:0.916394\n","[50]\tvalidation_0-aucpr:0.924863\n","[51]\tvalidation_0-aucpr:0.925454\n","[52]\tvalidation_0-aucpr:0.93337\n","[53]\tvalidation_0-aucpr:0.938775\n","[54]\tvalidation_0-aucpr:0.942129\n","[55]\tvalidation_0-aucpr:0.945037\n","[56]\tvalidation_0-aucpr:0.946714\n","[57]\tvalidation_0-aucpr:0.949776\n","[58]\tvalidation_0-aucpr:0.954407\n","[59]\tvalidation_0-aucpr:0.956481\n","[60]\tvalidation_0-aucpr:0.958096\n","[61]\tvalidation_0-aucpr:0.958449\n","[62]\tvalidation_0-aucpr:0.960664\n","[63]\tvalidation_0-aucpr:0.960706\n","[64]\tvalidation_0-aucpr:0.962463\n","[65]\tvalidation_0-aucpr:0.964735\n","[66]\tvalidation_0-aucpr:0.965246\n","[67]\tvalidation_0-aucpr:0.967706\n","[68]\tvalidation_0-aucpr:0.967662\n","[69]\tvalidation_0-aucpr:0.968623\n","[70]\tvalidation_0-aucpr:0.968352\n","[71]\tvalidation_0-aucpr:0.969991\n","[72]\tvalidation_0-aucpr:0.970259\n","[73]\tvalidation_0-aucpr:0.970163\n","[74]\tvalidation_0-aucpr:0.971082\n","[75]\tvalidation_0-aucpr:0.972311\n","[76]\tvalidation_0-aucpr:0.972522\n","[77]\tvalidation_0-aucpr:0.972436\n","[78]\tvalidation_0-aucpr:0.973757\n","[79]\tvalidation_0-aucpr:0.975134\n","[80]\tvalidation_0-aucpr:0.976516\n","[81]\tvalidation_0-aucpr:0.976542\n","[82]\tvalidation_0-aucpr:0.977391\n","[83]\tvalidation_0-aucpr:0.978055\n","[84]\tvalidation_0-aucpr:0.977801\n","[85]\tvalidation_0-aucpr:0.978262\n","[86]\tvalidation_0-aucpr:0.978663\n","[87]\tvalidation_0-aucpr:0.978239\n","[88]\tvalidation_0-aucpr:0.978942\n","[89]\tvalidation_0-aucpr:0.978322\n","[90]\tvalidation_0-aucpr:0.978614\n","[91]\tvalidation_0-aucpr:0.978653\n","[92]\tvalidation_0-aucpr:0.979184\n","[93]\tvalidation_0-aucpr:0.980835\n","[94]\tvalidation_0-aucpr:0.982334\n","[95]\tvalidation_0-aucpr:0.982348\n","[96]\tvalidation_0-aucpr:0.981991\n","[97]\tvalidation_0-aucpr:0.983393\n","[98]\tvalidation_0-aucpr:0.983402\n","[99]\tvalidation_0-aucpr:0.983756\n","[100]\tvalidation_0-aucpr:0.983658\n","[101]\tvalidation_0-aucpr:0.983987\n","[102]\tvalidation_0-aucpr:0.983913\n","[103]\tvalidation_0-aucpr:0.983917\n","[104]\tvalidation_0-aucpr:0.983757\n","[105]\tvalidation_0-aucpr:0.983319\n","[106]\tvalidation_0-aucpr:0.984473\n","[107]\tvalidation_0-aucpr:0.984116\n","[108]\tvalidation_0-aucpr:0.984008\n","[109]\tvalidation_0-aucpr:0.98396\n","[110]\tvalidation_0-aucpr:0.983622\n","[111]\tvalidation_0-aucpr:0.984051\n","[112]\tvalidation_0-aucpr:0.984053\n","[113]\tvalidation_0-aucpr:0.983914\n","[114]\tvalidation_0-aucpr:0.984236\n","Stopping. Best iteration:\n","[106]\tvalidation_0-aucpr:0.984473\n","\n","\n","Done with week 47\n","Starting week 48\n","\n","[0]\tvalidation_0-aucpr:0.813244\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.844403\n","[2]\tvalidation_0-aucpr:0.839734\n","[3]\tvalidation_0-aucpr:0.832995\n","[4]\tvalidation_0-aucpr:0.843186\n","[5]\tvalidation_0-aucpr:0.845169\n","[6]\tvalidation_0-aucpr:0.842151\n","[7]\tvalidation_0-aucpr:0.838921\n","[8]\tvalidation_0-aucpr:0.841878\n","[9]\tvalidation_0-aucpr:0.856904\n","[10]\tvalidation_0-aucpr:0.855993\n","[11]\tvalidation_0-aucpr:0.861487\n","[12]\tvalidation_0-aucpr:0.861326\n","[13]\tvalidation_0-aucpr:0.866599\n","[14]\tvalidation_0-aucpr:0.865288\n","[15]\tvalidation_0-aucpr:0.864242\n","[16]\tvalidation_0-aucpr:0.863512\n","[17]\tvalidation_0-aucpr:0.881734\n","[18]\tvalidation_0-aucpr:0.884103\n","[19]\tvalidation_0-aucpr:0.888268\n","[20]\tvalidation_0-aucpr:0.892939\n","[21]\tvalidation_0-aucpr:0.892062\n","[22]\tvalidation_0-aucpr:0.894511\n","[23]\tvalidation_0-aucpr:0.898055\n","[24]\tvalidation_0-aucpr:0.900648\n","[25]\tvalidation_0-aucpr:0.899639\n","[26]\tvalidation_0-aucpr:0.907154\n","[27]\tvalidation_0-aucpr:0.907801\n","[28]\tvalidation_0-aucpr:0.905663\n","[29]\tvalidation_0-aucpr:0.906743\n","[30]\tvalidation_0-aucpr:0.910184\n","[31]\tvalidation_0-aucpr:0.916088\n","[32]\tvalidation_0-aucpr:0.919553\n","[33]\tvalidation_0-aucpr:0.924645\n","[34]\tvalidation_0-aucpr:0.925482\n","[35]\tvalidation_0-aucpr:0.921617\n","[36]\tvalidation_0-aucpr:0.923623\n","[37]\tvalidation_0-aucpr:0.925177\n","[38]\tvalidation_0-aucpr:0.928541\n","[39]\tvalidation_0-aucpr:0.93453\n","[40]\tvalidation_0-aucpr:0.935011\n","[41]\tvalidation_0-aucpr:0.935345\n","[42]\tvalidation_0-aucpr:0.931651\n","[43]\tvalidation_0-aucpr:0.933228\n","[44]\tvalidation_0-aucpr:0.932387\n","[45]\tvalidation_0-aucpr:0.934038\n","[46]\tvalidation_0-aucpr:0.936058\n","[47]\tvalidation_0-aucpr:0.935549\n","[48]\tvalidation_0-aucpr:0.93714\n","[49]\tvalidation_0-aucpr:0.940588\n","[50]\tvalidation_0-aucpr:0.942308\n","[51]\tvalidation_0-aucpr:0.943067\n","[52]\tvalidation_0-aucpr:0.946364\n","[53]\tvalidation_0-aucpr:0.947728\n","[54]\tvalidation_0-aucpr:0.949355\n","[55]\tvalidation_0-aucpr:0.950833\n","[56]\tvalidation_0-aucpr:0.952628\n","[57]\tvalidation_0-aucpr:0.953213\n","[58]\tvalidation_0-aucpr:0.953654\n","[59]\tvalidation_0-aucpr:0.954208\n","[60]\tvalidation_0-aucpr:0.955623\n","[61]\tvalidation_0-aucpr:0.958295\n","[62]\tvalidation_0-aucpr:0.958408\n","[63]\tvalidation_0-aucpr:0.960179\n","[64]\tvalidation_0-aucpr:0.960344\n","[65]\tvalidation_0-aucpr:0.960489\n","[66]\tvalidation_0-aucpr:0.961897\n","[67]\tvalidation_0-aucpr:0.962125\n","[68]\tvalidation_0-aucpr:0.963587\n","[69]\tvalidation_0-aucpr:0.963198\n","[70]\tvalidation_0-aucpr:0.964708\n","[71]\tvalidation_0-aucpr:0.965559\n","[72]\tvalidation_0-aucpr:0.966912\n","[73]\tvalidation_0-aucpr:0.967987\n","[74]\tvalidation_0-aucpr:0.967731\n","[75]\tvalidation_0-aucpr:0.967837\n","[76]\tvalidation_0-aucpr:0.968425\n","[77]\tvalidation_0-aucpr:0.968842\n","[78]\tvalidation_0-aucpr:0.967723\n","[79]\tvalidation_0-aucpr:0.969011\n","[80]\tvalidation_0-aucpr:0.968656\n","[81]\tvalidation_0-aucpr:0.968242\n","[82]\tvalidation_0-aucpr:0.968267\n","[83]\tvalidation_0-aucpr:0.968397\n","[84]\tvalidation_0-aucpr:0.969216\n","[85]\tvalidation_0-aucpr:0.968763\n","[86]\tvalidation_0-aucpr:0.970164\n","[87]\tvalidation_0-aucpr:0.969769\n","[88]\tvalidation_0-aucpr:0.968793\n","[89]\tvalidation_0-aucpr:0.969219\n","[90]\tvalidation_0-aucpr:0.969244\n","[91]\tvalidation_0-aucpr:0.969346\n","[92]\tvalidation_0-aucpr:0.969516\n","[93]\tvalidation_0-aucpr:0.970054\n","[94]\tvalidation_0-aucpr:0.97012\n","Stopping. Best iteration:\n","[86]\tvalidation_0-aucpr:0.970164\n","\n","\n","Done with week 48\n","Starting week 49\n","\n","[0]\tvalidation_0-aucpr:0.833556\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.856046\n","[2]\tvalidation_0-aucpr:0.859146\n","[3]\tvalidation_0-aucpr:0.859632\n","[4]\tvalidation_0-aucpr:0.858708\n","[5]\tvalidation_0-aucpr:0.858354\n","[6]\tvalidation_0-aucpr:0.858036\n","[7]\tvalidation_0-aucpr:0.860487\n","[8]\tvalidation_0-aucpr:0.861037\n","[9]\tvalidation_0-aucpr:0.866168\n","[10]\tvalidation_0-aucpr:0.866383\n","[11]\tvalidation_0-aucpr:0.865573\n","[12]\tvalidation_0-aucpr:0.880818\n","[13]\tvalidation_0-aucpr:0.890535\n","[14]\tvalidation_0-aucpr:0.884402\n","[15]\tvalidation_0-aucpr:0.893819\n","[16]\tvalidation_0-aucpr:0.902178\n","[17]\tvalidation_0-aucpr:0.910912\n","[18]\tvalidation_0-aucpr:0.907823\n","[19]\tvalidation_0-aucpr:0.904241\n","[20]\tvalidation_0-aucpr:0.91236\n","[21]\tvalidation_0-aucpr:0.911986\n","[22]\tvalidation_0-aucpr:0.914743\n","[23]\tvalidation_0-aucpr:0.915441\n","[24]\tvalidation_0-aucpr:0.919579\n","[25]\tvalidation_0-aucpr:0.921634\n","[26]\tvalidation_0-aucpr:0.920825\n","[27]\tvalidation_0-aucpr:0.927127\n","[28]\tvalidation_0-aucpr:0.925893\n","[29]\tvalidation_0-aucpr:0.927173\n","[30]\tvalidation_0-aucpr:0.928445\n","[31]\tvalidation_0-aucpr:0.930197\n","[32]\tvalidation_0-aucpr:0.927828\n","[33]\tvalidation_0-aucpr:0.927024\n","[34]\tvalidation_0-aucpr:0.931286\n","[35]\tvalidation_0-aucpr:0.930623\n","[36]\tvalidation_0-aucpr:0.927848\n","[37]\tvalidation_0-aucpr:0.929635\n","[38]\tvalidation_0-aucpr:0.929105\n","[39]\tvalidation_0-aucpr:0.931576\n","[40]\tvalidation_0-aucpr:0.930528\n","[41]\tvalidation_0-aucpr:0.929408\n","[42]\tvalidation_0-aucpr:0.931312\n","[43]\tvalidation_0-aucpr:0.930907\n","[44]\tvalidation_0-aucpr:0.930881\n","[45]\tvalidation_0-aucpr:0.929657\n","[46]\tvalidation_0-aucpr:0.932761\n","[47]\tvalidation_0-aucpr:0.931413\n","[48]\tvalidation_0-aucpr:0.931104\n","[49]\tvalidation_0-aucpr:0.929298\n","[50]\tvalidation_0-aucpr:0.928469\n","[51]\tvalidation_0-aucpr:0.928436\n","[52]\tvalidation_0-aucpr:0.929639\n","[53]\tvalidation_0-aucpr:0.932473\n","[54]\tvalidation_0-aucpr:0.931837\n","Stopping. Best iteration:\n","[46]\tvalidation_0-aucpr:0.932761\n","\n","\n","Done with week 49\n","Starting week 50\n","\n","[0]\tvalidation_0-aucpr:0.842568\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.852555\n","[2]\tvalidation_0-aucpr:0.854469\n","[3]\tvalidation_0-aucpr:0.852445\n","[4]\tvalidation_0-aucpr:0.897621\n","[5]\tvalidation_0-aucpr:0.895727\n","[6]\tvalidation_0-aucpr:0.897521\n","[7]\tvalidation_0-aucpr:0.899751\n","[8]\tvalidation_0-aucpr:0.898925\n","[9]\tvalidation_0-aucpr:0.902508\n","[10]\tvalidation_0-aucpr:0.901792\n","[11]\tvalidation_0-aucpr:0.903668\n","[12]\tvalidation_0-aucpr:0.911865\n","[13]\tvalidation_0-aucpr:0.9095\n","[14]\tvalidation_0-aucpr:0.907586\n","[15]\tvalidation_0-aucpr:0.910248\n","[16]\tvalidation_0-aucpr:0.91786\n","[17]\tvalidation_0-aucpr:0.923745\n","[18]\tvalidation_0-aucpr:0.928516\n","[19]\tvalidation_0-aucpr:0.925944\n","[20]\tvalidation_0-aucpr:0.928285\n","[21]\tvalidation_0-aucpr:0.928744\n","[22]\tvalidation_0-aucpr:0.932149\n","[23]\tvalidation_0-aucpr:0.934283\n","[24]\tvalidation_0-aucpr:0.933798\n","[25]\tvalidation_0-aucpr:0.935459\n","[26]\tvalidation_0-aucpr:0.934633\n","[27]\tvalidation_0-aucpr:0.931534\n","[28]\tvalidation_0-aucpr:0.93984\n","[29]\tvalidation_0-aucpr:0.935053\n","[30]\tvalidation_0-aucpr:0.939049\n","[31]\tvalidation_0-aucpr:0.939534\n","[32]\tvalidation_0-aucpr:0.938449\n","[33]\tvalidation_0-aucpr:0.942106\n","[34]\tvalidation_0-aucpr:0.941223\n","[35]\tvalidation_0-aucpr:0.942545\n","[36]\tvalidation_0-aucpr:0.941332\n","[37]\tvalidation_0-aucpr:0.943752\n","[38]\tvalidation_0-aucpr:0.944506\n","[39]\tvalidation_0-aucpr:0.948087\n","[40]\tvalidation_0-aucpr:0.94971\n","[41]\tvalidation_0-aucpr:0.948873\n","[42]\tvalidation_0-aucpr:0.946661\n","[43]\tvalidation_0-aucpr:0.947817\n","[44]\tvalidation_0-aucpr:0.948593\n","[45]\tvalidation_0-aucpr:0.947235\n","[46]\tvalidation_0-aucpr:0.948836\n","[47]\tvalidation_0-aucpr:0.951548\n","[48]\tvalidation_0-aucpr:0.951374\n","[49]\tvalidation_0-aucpr:0.955728\n","[50]\tvalidation_0-aucpr:0.955517\n","[51]\tvalidation_0-aucpr:0.959528\n","[52]\tvalidation_0-aucpr:0.957549\n","[53]\tvalidation_0-aucpr:0.958638\n","[54]\tvalidation_0-aucpr:0.959219\n","[55]\tvalidation_0-aucpr:0.961196\n","[56]\tvalidation_0-aucpr:0.963919\n","[57]\tvalidation_0-aucpr:0.964396\n","[58]\tvalidation_0-aucpr:0.966033\n","[59]\tvalidation_0-aucpr:0.970031\n","[60]\tvalidation_0-aucpr:0.970599\n","[61]\tvalidation_0-aucpr:0.971062\n","[62]\tvalidation_0-aucpr:0.972265\n","[63]\tvalidation_0-aucpr:0.972395\n","[64]\tvalidation_0-aucpr:0.973004\n","[65]\tvalidation_0-aucpr:0.973555\n","[66]\tvalidation_0-aucpr:0.973662\n","[67]\tvalidation_0-aucpr:0.973948\n","[68]\tvalidation_0-aucpr:0.974409\n","[69]\tvalidation_0-aucpr:0.974761\n","[70]\tvalidation_0-aucpr:0.973752\n","[71]\tvalidation_0-aucpr:0.974584\n","[72]\tvalidation_0-aucpr:0.974908\n","[73]\tvalidation_0-aucpr:0.975224\n","[74]\tvalidation_0-aucpr:0.976523\n","[75]\tvalidation_0-aucpr:0.977124\n","[76]\tvalidation_0-aucpr:0.978743\n","[77]\tvalidation_0-aucpr:0.977835\n","[78]\tvalidation_0-aucpr:0.979698\n","[79]\tvalidation_0-aucpr:0.979892\n","[80]\tvalidation_0-aucpr:0.980093\n","[81]\tvalidation_0-aucpr:0.979528\n","[82]\tvalidation_0-aucpr:0.980408\n","[83]\tvalidation_0-aucpr:0.980369\n","[84]\tvalidation_0-aucpr:0.978827\n","[85]\tvalidation_0-aucpr:0.979354\n","[86]\tvalidation_0-aucpr:0.979707\n","[87]\tvalidation_0-aucpr:0.980497\n","[88]\tvalidation_0-aucpr:0.981257\n","[89]\tvalidation_0-aucpr:0.981721\n","[90]\tvalidation_0-aucpr:0.981483\n","[91]\tvalidation_0-aucpr:0.980736\n","[92]\tvalidation_0-aucpr:0.981971\n","[93]\tvalidation_0-aucpr:0.982763\n","[94]\tvalidation_0-aucpr:0.982418\n","[95]\tvalidation_0-aucpr:0.983019\n","[96]\tvalidation_0-aucpr:0.983223\n","[97]\tvalidation_0-aucpr:0.984024\n","[98]\tvalidation_0-aucpr:0.984493\n","[99]\tvalidation_0-aucpr:0.984696\n","[100]\tvalidation_0-aucpr:0.985211\n","[101]\tvalidation_0-aucpr:0.985097\n","[102]\tvalidation_0-aucpr:0.984542\n","[103]\tvalidation_0-aucpr:0.984982\n","[104]\tvalidation_0-aucpr:0.985289\n","[105]\tvalidation_0-aucpr:0.985918\n","[106]\tvalidation_0-aucpr:0.985225\n","[107]\tvalidation_0-aucpr:0.984975\n","[108]\tvalidation_0-aucpr:0.984632\n","[109]\tvalidation_0-aucpr:0.985226\n","[110]\tvalidation_0-aucpr:0.984931\n","[111]\tvalidation_0-aucpr:0.985917\n","[112]\tvalidation_0-aucpr:0.986016\n","[113]\tvalidation_0-aucpr:0.986447\n","[114]\tvalidation_0-aucpr:0.986058\n","[115]\tvalidation_0-aucpr:0.985908\n","[116]\tvalidation_0-aucpr:0.986336\n","[117]\tvalidation_0-aucpr:0.98617\n","[118]\tvalidation_0-aucpr:0.986442\n","[119]\tvalidation_0-aucpr:0.986272\n","[120]\tvalidation_0-aucpr:0.986589\n","[121]\tvalidation_0-aucpr:0.987312\n","[122]\tvalidation_0-aucpr:0.987146\n","[123]\tvalidation_0-aucpr:0.98762\n","[124]\tvalidation_0-aucpr:0.987635\n","[125]\tvalidation_0-aucpr:0.987549\n","[126]\tvalidation_0-aucpr:0.987681\n","[127]\tvalidation_0-aucpr:0.988193\n","[128]\tvalidation_0-aucpr:0.987767\n","[129]\tvalidation_0-aucpr:0.987908\n","[130]\tvalidation_0-aucpr:0.988107\n","[131]\tvalidation_0-aucpr:0.988589\n","[132]\tvalidation_0-aucpr:0.988979\n","[133]\tvalidation_0-aucpr:0.989167\n","[134]\tvalidation_0-aucpr:0.988916\n","[135]\tvalidation_0-aucpr:0.988282\n","[136]\tvalidation_0-aucpr:0.988707\n","[137]\tvalidation_0-aucpr:0.988945\n","[138]\tvalidation_0-aucpr:0.988956\n","[139]\tvalidation_0-aucpr:0.98849\n","[140]\tvalidation_0-aucpr:0.988981\n","[141]\tvalidation_0-aucpr:0.988868\n","Stopping. Best iteration:\n","[133]\tvalidation_0-aucpr:0.989167\n","\n","\n","Done with week 50\n","Starting week 51\n","\n","[0]\tvalidation_0-aucpr:0.782526\n","Will train until validation_0-aucpr hasn't improved in 8 rounds.\n","[1]\tvalidation_0-aucpr:0.783409\n","[2]\tvalidation_0-aucpr:0.811963\n","[3]\tvalidation_0-aucpr:0.829123\n","[4]\tvalidation_0-aucpr:0.855783\n","[5]\tvalidation_0-aucpr:0.863915\n","[6]\tvalidation_0-aucpr:0.863359\n","[7]\tvalidation_0-aucpr:0.862354\n","[8]\tvalidation_0-aucpr:0.860451\n","[9]\tvalidation_0-aucpr:0.862315\n","[10]\tvalidation_0-aucpr:0.860383\n","[11]\tvalidation_0-aucpr:0.86002\n","[12]\tvalidation_0-aucpr:0.872112\n","[13]\tvalidation_0-aucpr:0.890059\n","[14]\tvalidation_0-aucpr:0.895628\n","[15]\tvalidation_0-aucpr:0.899978\n","[16]\tvalidation_0-aucpr:0.904228\n","[17]\tvalidation_0-aucpr:0.903058\n","[18]\tvalidation_0-aucpr:0.907665\n","[19]\tvalidation_0-aucpr:0.905353\n","[20]\tvalidation_0-aucpr:0.903494\n","[21]\tvalidation_0-aucpr:0.906788\n","[22]\tvalidation_0-aucpr:0.913168\n","[23]\tvalidation_0-aucpr:0.913311\n","[24]\tvalidation_0-aucpr:0.914923\n","[25]\tvalidation_0-aucpr:0.917644\n","[26]\tvalidation_0-aucpr:0.919048\n","[27]\tvalidation_0-aucpr:0.919393\n","[28]\tvalidation_0-aucpr:0.92104\n","[29]\tvalidation_0-aucpr:0.920269\n","[30]\tvalidation_0-aucpr:0.92198\n","[31]\tvalidation_0-aucpr:0.922363\n","[32]\tvalidation_0-aucpr:0.924554\n","[33]\tvalidation_0-aucpr:0.926248\n","[34]\tvalidation_0-aucpr:0.929758\n","[35]\tvalidation_0-aucpr:0.929125\n","[36]\tvalidation_0-aucpr:0.93022\n","[37]\tvalidation_0-aucpr:0.931224\n","[38]\tvalidation_0-aucpr:0.934404\n","[39]\tvalidation_0-aucpr:0.935568\n","[40]\tvalidation_0-aucpr:0.938226\n","[41]\tvalidation_0-aucpr:0.939765\n","[42]\tvalidation_0-aucpr:0.940437\n","[43]\tvalidation_0-aucpr:0.941951\n","[44]\tvalidation_0-aucpr:0.943664\n","[45]\tvalidation_0-aucpr:0.946953\n","[46]\tvalidation_0-aucpr:0.950929\n","[47]\tvalidation_0-aucpr:0.952498\n","[48]\tvalidation_0-aucpr:0.954169\n","[49]\tvalidation_0-aucpr:0.955422\n","[50]\tvalidation_0-aucpr:0.958377\n","[51]\tvalidation_0-aucpr:0.959265\n","[52]\tvalidation_0-aucpr:0.961679\n","[53]\tvalidation_0-aucpr:0.96566\n","[54]\tvalidation_0-aucpr:0.968833\n","[55]\tvalidation_0-aucpr:0.970476\n","[56]\tvalidation_0-aucpr:0.972172\n","[57]\tvalidation_0-aucpr:0.972152\n","[58]\tvalidation_0-aucpr:0.973635\n","[59]\tvalidation_0-aucpr:0.972353\n","[60]\tvalidation_0-aucpr:0.973655\n","[61]\tvalidation_0-aucpr:0.974729\n","[62]\tvalidation_0-aucpr:0.97506\n","[63]\tvalidation_0-aucpr:0.976027\n","[64]\tvalidation_0-aucpr:0.976685\n","[65]\tvalidation_0-aucpr:0.977546\n","[66]\tvalidation_0-aucpr:0.97776\n","[67]\tvalidation_0-aucpr:0.978571\n","[68]\tvalidation_0-aucpr:0.978143\n","[69]\tvalidation_0-aucpr:0.978855\n","[70]\tvalidation_0-aucpr:0.979242\n","[71]\tvalidation_0-aucpr:0.977989\n","[72]\tvalidation_0-aucpr:0.980467\n","[73]\tvalidation_0-aucpr:0.981281\n","[74]\tvalidation_0-aucpr:0.98161\n","[75]\tvalidation_0-aucpr:0.981064\n","[76]\tvalidation_0-aucpr:0.981331\n","[77]\tvalidation_0-aucpr:0.98197\n","[78]\tvalidation_0-aucpr:0.980676\n","[79]\tvalidation_0-aucpr:0.981002\n","[80]\tvalidation_0-aucpr:0.982165\n","[81]\tvalidation_0-aucpr:0.981735\n","[82]\tvalidation_0-aucpr:0.982271\n","[83]\tvalidation_0-aucpr:0.981891\n","[84]\tvalidation_0-aucpr:0.982296\n","[85]\tvalidation_0-aucpr:0.982518\n","[86]\tvalidation_0-aucpr:0.982842\n","[87]\tvalidation_0-aucpr:0.983098\n","[88]\tvalidation_0-aucpr:0.983737\n","[89]\tvalidation_0-aucpr:0.983201\n","[90]\tvalidation_0-aucpr:0.982306\n","[91]\tvalidation_0-aucpr:0.983159\n","[92]\tvalidation_0-aucpr:0.984221\n","[93]\tvalidation_0-aucpr:0.984046\n","[94]\tvalidation_0-aucpr:0.983709\n","[95]\tvalidation_0-aucpr:0.983782\n","[96]\tvalidation_0-aucpr:0.983299\n","[97]\tvalidation_0-aucpr:0.983436\n","[98]\tvalidation_0-aucpr:0.983138\n","[99]\tvalidation_0-aucpr:0.983696\n","[100]\tvalidation_0-aucpr:0.98361\n","Stopping. Best iteration:\n","[92]\tvalidation_0-aucpr:0.984221\n","\n","\n","Done with week 51\n"]}]},{"cell_type":"code","source":["print(error_log)\n","\n","simulation_column_titles = ['week', 'number_training', 'precision', 'recall', 'fscore', 'confusion_matrix', 'pos_ratio', 'false_pos_rate']\n","\n","simulation_stats_df = pd.DataFrame(simulation_data, columns = simulation_column_titles)\n","simulation_stats_df"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"yrHwkGEfDXnd","executionInfo":{"status":"ok","timestamp":1652037350558,"user_tz":240,"elapsed":172,"user":{"displayName":"Luke Muther","userId":"09562218690618723932"}},"outputId":"a0b65453-2fc7-4a61-bef8-c53374392d16"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Error:\"'[-13 -12 -11 -10  -9  -8  -7  -6  -5  -4  -3  -2  -1] not found in axis'\" at week 10\n","Error:\"'[-13 -12 -11 -10  -9  -8  -7  -6  -5  -4  -3  -2  -1] not found in axis'\" at week 25\n","\n"]},{"output_type":"execute_result","data":{"text/plain":["       week  number_training  precision    recall    fscore  \\\n","0    Week 2              162   0.956275  0.961326  0.957626   \n","1    Week 3              347   0.953267  0.952128  0.952640   \n","2    Week 4              532   0.950667  0.933333  0.939750   \n","3    Week 5              703   0.923744  0.932642  0.924568   \n","4    Week 6              874   0.976258  0.974093  0.975055   \n","5    Week 7             1063   0.978758  0.979275  0.978685   \n","6    Week 8             1237   0.991940  0.989637  0.990257   \n","7    Week 9             1412   0.989744  0.989744  0.989744   \n","8   Week 11             1755   0.971841  0.972527  0.972095   \n","9   Week 12             1928   0.990106  0.990000  0.989642   \n","10  Week 13             2144   0.984308  0.984536  0.984349   \n","11  Week 14             2351   0.954689  0.953368  0.953968   \n","12  Week 15             2483   0.994793  0.994764  0.994618   \n","13  Week 16             2676   0.978142  0.978142  0.978142   \n","14  Week 17             2862   0.995419  0.994764  0.994932   \n","15  Week 18             3056   0.979275  0.979275  0.979275   \n","16  Week 19             3163   0.994654  0.994624  0.994424   \n","17  Week 20             3350   0.976094  0.975369  0.975669   \n","18  Week 21             3594   0.985610  0.984127  0.984716   \n","19  Week 22             3680   0.935848  0.938462  0.936926   \n","20  Week 23             3945   0.984380  0.984127  0.979429   \n","21  Week 24             4124   0.969697  0.969697  0.969697   \n","22  Week 26             4490   0.967934  0.959184  0.961749   \n","23  Week 27             4696   0.989305  0.989305  0.989305   \n","24  Week 28             4823   0.970907  0.961326  0.964370   \n","25  Week 29             5009   0.991071  0.989796  0.990108   \n","26  Week 30             5185   0.967033  0.967033  0.967033   \n","27  Week 31             5343   0.978452  0.974747  0.975950   \n","28  Week 32             5596   0.995264  0.994475  0.994680   \n","29  Week 33             5741   0.985545  0.985075  0.985245   \n","30  Week 34             5950   0.989189  0.989189  0.989189   \n","31  Week 35             6094   0.957153  0.956098  0.956573   \n","32  Week 36             6275   0.991296  0.989362  0.989864   \n","33  Week 37             6402   0.983479  0.979592  0.980551   \n","34  Week 38             6617   0.995443  0.994792  0.994958   \n","35  Week 39             6784   0.984749  0.983957  0.984255   \n","36  Week 40             6906   0.995604  0.994872  0.995062   \n","37  Week 41             7182   0.984690  0.983957  0.984231   \n","38  Week 42             7300   0.981884  0.980296  0.980822   \n","39  Week 43             7506   0.991087  0.989305  0.989761   \n","40  Week 44             7742   0.987864  0.985437  0.986041   \n","41  Week 45             7861   0.994625  0.994595  0.994443   \n","42  Week 46             8048   0.990809  0.989583  0.989879   \n","43  Week 47             8227   0.995660  0.994792  0.995021   \n","44  Week 48             8354   0.985415  0.984848  0.985057   \n","45  Week 49             8592   0.989362  0.989362  0.989362   \n","46  Week 50             8721   0.987013  0.984848  0.985368   \n","47  Week 51             8977   0.995195  0.994595  0.994746   \n","\n","        confusion_matrix  pos_ratio  false_pos_rate  \n","0     [[170, 2], [5, 4]]   0.500000        0.555556  \n","1    [[163, 5], [4, 16]]   0.312500        0.200000  \n","2   [[172, 10], [3, 10]]   1.000000        0.230769  \n","3    [[173, 3], [10, 7]]   0.428571        0.588235  \n","4     [[184, 3], [2, 4]]   0.750000        0.333333  \n","5    [[175, 1], [3, 14]]   0.071429        0.176471  \n","6     [[184, 2], [0, 7]]   0.285714        0.000000  \n","7    [[181, 1], [1, 12]]   0.083333        0.076923  \n","8    [[165, 2], [3, 12]]   0.166667        0.200000  \n","9    [[186, 0], [2, 12]]   0.000000        0.142857  \n","10   [[174, 1], [2, 17]]   0.058824        0.105263  \n","11   [[171, 5], [4, 13]]   0.384615        0.235294  \n","12    [[182, 0], [1, 8]]   0.000000        0.111111  \n","13   [[167, 2], [2, 12]]   0.166667        0.142857  \n","14    [[183, 1], [0, 7]]   0.142857        0.000000  \n","15    [[180, 2], [2, 9]]   0.222222        0.181818  \n","16    [[179, 0], [1, 6]]   0.000000        0.142857  \n","17   [[182, 3], [2, 16]]   0.187500        0.111111  \n","18    [[181, 2], [1, 5]]   0.400000        0.166667  \n","19   [[171, 5], [7, 12]]   0.416667        0.368421  \n","20    [[185, 0], [3, 1]]   0.000000        0.750000  \n","21   [[180, 3], [3, 12]]   0.250000        0.200000  \n","22   [[171, 7], [1, 17]]   0.411765        0.055556  \n","23    [[177, 1], [1, 8]]   0.125000        0.111111  \n","24   [[163, 6], [1, 11]]   0.545455        0.083333  \n","25   [[180, 2], [0, 14]]   0.142857        0.000000  \n","26    [[167, 3], [3, 9]]   0.333333        0.250000  \n","27   [[181, 4], [1, 12]]   0.333333        0.076923  \n","28    [[174, 1], [0, 6]]   0.166667        0.000000  \n","29   [[180, 2], [1, 18]]   0.111111        0.052632  \n","30    [[181, 1], [1, 2]]   0.500000        0.333333  \n","31   [[180, 5], [4, 16]]   0.312500        0.200000  \n","32    [[177, 2], [0, 9]]   0.222222        0.000000  \n","33   [[175, 4], [0, 17]]   0.235294        0.000000  \n","34    [[184, 1], [0, 7]]   0.142857        0.000000  \n","35   [[173, 2], [1, 11]]   0.181818        0.083333  \n","36    [[188, 1], [0, 6]]   0.166667        0.000000  \n","37   [[172, 2], [1, 12]]   0.166667        0.076923  \n","38   [[184, 3], [1, 15]]   0.200000        0.062500  \n","39   [[175, 2], [0, 10]]   0.200000        0.000000  \n","40   [[188, 3], [0, 15]]   0.200000        0.000000  \n","41    [[176, 0], [1, 8]]   0.000000        0.111111  \n","42   [[175, 2], [0, 15]]   0.133333        0.000000  \n","43    [[186, 1], [0, 5]]   0.200000        0.000000  \n","44   [[180, 2], [1, 15]]   0.133333        0.062500  \n","45    [[178, 1], [1, 8]]   0.125000        0.111111  \n","46   [[177, 3], [0, 18]]   0.166667        0.000000  \n","47    [[176, 1], [0, 8]]   0.125000        0.000000  "],"text/html":["\n","  <div id=\"df-9a8e1bd0-42c4-41c4-b16f-b360283b6af2\">\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>week</th>\n","      <th>number_training</th>\n","      <th>precision</th>\n","      <th>recall</th>\n","      <th>fscore</th>\n","      <th>confusion_matrix</th>\n","      <th>pos_ratio</th>\n","      <th>false_pos_rate</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Week 2</td>\n","      <td>162</td>\n","      <td>0.956275</td>\n","      <td>0.961326</td>\n","      <td>0.957626</td>\n","      <td>[[170, 2], [5, 4]]</td>\n","      <td>0.500000</td>\n","      <td>0.555556</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Week 3</td>\n","      <td>347</td>\n","      <td>0.953267</td>\n","      <td>0.952128</td>\n","      <td>0.952640</td>\n","      <td>[[163, 5], [4, 16]]</td>\n","      <td>0.312500</td>\n","      <td>0.200000</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Week 4</td>\n","      <td>532</td>\n","      <td>0.950667</td>\n","      <td>0.933333</td>\n","      <td>0.939750</td>\n","      <td>[[172, 10], [3, 10]]</td>\n","      <td>1.000000</td>\n","      <td>0.230769</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Week 5</td>\n","      <td>703</td>\n","      <td>0.923744</td>\n","      <td>0.932642</td>\n","      <td>0.924568</td>\n","      <td>[[173, 3], [10, 7]]</td>\n","      <td>0.428571</td>\n","      <td>0.588235</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Week 6</td>\n","      <td>874</td>\n","      <td>0.976258</td>\n","      <td>0.974093</td>\n","      <td>0.975055</td>\n","      <td>[[184, 3], [2, 4]]</td>\n","      <td>0.750000</td>\n","      <td>0.333333</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>Week 7</td>\n","      <td>1063</td>\n","      <td>0.978758</td>\n","      <td>0.979275</td>\n","      <td>0.978685</td>\n","      <td>[[175, 1], [3, 14]]</td>\n","      <td>0.071429</td>\n","      <td>0.176471</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>Week 8</td>\n","      <td>1237</td>\n","      <td>0.991940</td>\n","      <td>0.989637</td>\n","      <td>0.990257</td>\n","      <td>[[184, 2], [0, 7]]</td>\n","      <td>0.285714</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>Week 9</td>\n","      <td>1412</td>\n","      <td>0.989744</td>\n","      <td>0.989744</td>\n","      <td>0.989744</td>\n","      <td>[[181, 1], [1, 12]]</td>\n","      <td>0.083333</td>\n","      <td>0.076923</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>Week 11</td>\n","      <td>1755</td>\n","      <td>0.971841</td>\n","      <td>0.972527</td>\n","      <td>0.972095</td>\n","      <td>[[165, 2], [3, 12]]</td>\n","      <td>0.166667</td>\n","      <td>0.200000</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>Week 12</td>\n","      <td>1928</td>\n","      <td>0.990106</td>\n","      <td>0.990000</td>\n","      <td>0.989642</td>\n","      <td>[[186, 0], [2, 12]]</td>\n","      <td>0.000000</td>\n","      <td>0.142857</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>Week 13</td>\n","      <td>2144</td>\n","      <td>0.984308</td>\n","      <td>0.984536</td>\n","      <td>0.984349</td>\n","      <td>[[174, 1], [2, 17]]</td>\n","      <td>0.058824</td>\n","      <td>0.105263</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>Week 14</td>\n","      <td>2351</td>\n","      <td>0.954689</td>\n","      <td>0.953368</td>\n","      <td>0.953968</td>\n","      <td>[[171, 5], [4, 13]]</td>\n","      <td>0.384615</td>\n","      <td>0.235294</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>Week 15</td>\n","      <td>2483</td>\n","      <td>0.994793</td>\n","      <td>0.994764</td>\n","      <td>0.994618</td>\n","      <td>[[182, 0], [1, 8]]</td>\n","      <td>0.000000</td>\n","      <td>0.111111</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>Week 16</td>\n","      <td>2676</td>\n","      <td>0.978142</td>\n","      <td>0.978142</td>\n","      <td>0.978142</td>\n","      <td>[[167, 2], [2, 12]]</td>\n","      <td>0.166667</td>\n","      <td>0.142857</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>Week 17</td>\n","      <td>2862</td>\n","      <td>0.995419</td>\n","      <td>0.994764</td>\n","      <td>0.994932</td>\n","      <td>[[183, 1], [0, 7]]</td>\n","      <td>0.142857</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>Week 18</td>\n","      <td>3056</td>\n","      <td>0.979275</td>\n","      <td>0.979275</td>\n","      <td>0.979275</td>\n","      <td>[[180, 2], [2, 9]]</td>\n","      <td>0.222222</td>\n","      <td>0.181818</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>Week 19</td>\n","      <td>3163</td>\n","      <td>0.994654</td>\n","      <td>0.994624</td>\n","      <td>0.994424</td>\n","      <td>[[179, 0], [1, 6]]</td>\n","      <td>0.000000</td>\n","      <td>0.142857</td>\n","    </tr>\n","    <tr>\n","      <th>17</th>\n","      <td>Week 20</td>\n","      <td>3350</td>\n","      <td>0.976094</td>\n","      <td>0.975369</td>\n","      <td>0.975669</td>\n","      <td>[[182, 3], [2, 16]]</td>\n","      <td>0.187500</td>\n","      <td>0.111111</td>\n","    </tr>\n","    <tr>\n","      <th>18</th>\n","      <td>Week 21</td>\n","      <td>3594</td>\n","      <td>0.985610</td>\n","      <td>0.984127</td>\n","      <td>0.984716</td>\n","      <td>[[181, 2], [1, 5]]</td>\n","      <td>0.400000</td>\n","      <td>0.166667</td>\n","    </tr>\n","    <tr>\n","      <th>19</th>\n","      <td>Week 22</td>\n","      <td>3680</td>\n","      <td>0.935848</td>\n","      <td>0.938462</td>\n","      <td>0.936926</td>\n","      <td>[[171, 5], [7, 12]]</td>\n","      <td>0.416667</td>\n","      <td>0.368421</td>\n","    </tr>\n","    <tr>\n","      <th>20</th>\n","      <td>Week 23</td>\n","      <td>3945</td>\n","      <td>0.984380</td>\n","      <td>0.984127</td>\n","      <td>0.979429</td>\n","      <td>[[185, 0], [3, 1]]</td>\n","      <td>0.000000</td>\n","      <td>0.750000</td>\n","    </tr>\n","    <tr>\n","      <th>21</th>\n","      <td>Week 24</td>\n","      <td>4124</td>\n","      <td>0.969697</td>\n","      <td>0.969697</td>\n","      <td>0.969697</td>\n","      <td>[[180, 3], [3, 12]]</td>\n","      <td>0.250000</td>\n","      <td>0.200000</td>\n","    </tr>\n","    <tr>\n","      <th>22</th>\n","      <td>Week 26</td>\n","      <td>4490</td>\n","      <td>0.967934</td>\n","      <td>0.959184</td>\n","      <td>0.961749</td>\n","      <td>[[171, 7], [1, 17]]</td>\n","      <td>0.411765</td>\n","      <td>0.055556</td>\n","    </tr>\n","    <tr>\n","      <th>23</th>\n","      <td>Week 27</td>\n","      <td>4696</td>\n","      <td>0.989305</td>\n","      <td>0.989305</td>\n","      <td>0.989305</td>\n","      <td>[[177, 1], [1, 8]]</td>\n","      <td>0.125000</td>\n","      <td>0.111111</td>\n","    </tr>\n","    <tr>\n","      <th>24</th>\n","      <td>Week 28</td>\n","      <td>4823</td>\n","      <td>0.970907</td>\n","      <td>0.961326</td>\n","      <td>0.964370</td>\n","      <td>[[163, 6], [1, 11]]</td>\n","      <td>0.545455</td>\n","      <td>0.083333</td>\n","    </tr>\n","    <tr>\n","      <th>25</th>\n","      <td>Week 29</td>\n","      <td>5009</td>\n","      <td>0.991071</td>\n","      <td>0.989796</td>\n","      <td>0.990108</td>\n","      <td>[[180, 2], [0, 14]]</td>\n","      <td>0.142857</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>26</th>\n","      <td>Week 30</td>\n","      <td>5185</td>\n","      <td>0.967033</td>\n","      <td>0.967033</td>\n","      <td>0.967033</td>\n","      <td>[[167, 3], [3, 9]]</td>\n","      <td>0.333333</td>\n","      <td>0.250000</td>\n","    </tr>\n","    <tr>\n","      <th>27</th>\n","      <td>Week 31</td>\n","      <td>5343</td>\n","      <td>0.978452</td>\n","      <td>0.974747</td>\n","      <td>0.975950</td>\n","      <td>[[181, 4], [1, 12]]</td>\n","      <td>0.333333</td>\n","      <td>0.076923</td>\n","    </tr>\n","    <tr>\n","      <th>28</th>\n","      <td>Week 32</td>\n","      <td>5596</td>\n","      <td>0.995264</td>\n","      <td>0.994475</td>\n","      <td>0.994680</td>\n","      <td>[[174, 1], [0, 6]]</td>\n","      <td>0.166667</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>29</th>\n","      <td>Week 33</td>\n","      <td>5741</td>\n","      <td>0.985545</td>\n","      <td>0.985075</td>\n","      <td>0.985245</td>\n","      <td>[[180, 2], [1, 18]]</td>\n","      <td>0.111111</td>\n","      <td>0.052632</td>\n","    </tr>\n","    <tr>\n","      <th>30</th>\n","      <td>Week 34</td>\n","      <td>5950</td>\n","      <td>0.989189</td>\n","      <td>0.989189</td>\n","      <td>0.989189</td>\n","      <td>[[181, 1], [1, 2]]</td>\n","      <td>0.500000</td>\n","      <td>0.333333</td>\n","    </tr>\n","    <tr>\n","      <th>31</th>\n","      <td>Week 35</td>\n","      <td>6094</td>\n","      <td>0.957153</td>\n","      <td>0.956098</td>\n","      <td>0.956573</td>\n","      <td>[[180, 5], [4, 16]]</td>\n","      <td>0.312500</td>\n","      <td>0.200000</td>\n","    </tr>\n","    <tr>\n","      <th>32</th>\n","      <td>Week 36</td>\n","      <td>6275</td>\n","      <td>0.991296</td>\n","      <td>0.989362</td>\n","      <td>0.989864</td>\n","      <td>[[177, 2], [0, 9]]</td>\n","      <td>0.222222</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>33</th>\n","      <td>Week 37</td>\n","      <td>6402</td>\n","      <td>0.983479</td>\n","      <td>0.979592</td>\n","      <td>0.980551</td>\n","      <td>[[175, 4], [0, 17]]</td>\n","      <td>0.235294</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>34</th>\n","      <td>Week 38</td>\n","      <td>6617</td>\n","      <td>0.995443</td>\n","      <td>0.994792</td>\n","      <td>0.994958</td>\n","      <td>[[184, 1], [0, 7]]</td>\n","      <td>0.142857</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>35</th>\n","      <td>Week 39</td>\n","      <td>6784</td>\n","      <td>0.984749</td>\n","      <td>0.983957</td>\n","      <td>0.984255</td>\n","      <td>[[173, 2], [1, 11]]</td>\n","      <td>0.181818</td>\n","      <td>0.083333</td>\n","    </tr>\n","    <tr>\n","      <th>36</th>\n","      <td>Week 40</td>\n","      <td>6906</td>\n","      <td>0.995604</td>\n","      <td>0.994872</td>\n","      <td>0.995062</td>\n","      <td>[[188, 1], [0, 6]]</td>\n","      <td>0.166667</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>37</th>\n","      <td>Week 41</td>\n","      <td>7182</td>\n","      <td>0.984690</td>\n","      <td>0.983957</td>\n","      <td>0.984231</td>\n","      <td>[[172, 2], [1, 12]]</td>\n","      <td>0.166667</td>\n","      <td>0.076923</td>\n","    </tr>\n","    <tr>\n","      <th>38</th>\n","      <td>Week 42</td>\n","      <td>7300</td>\n","      <td>0.981884</td>\n","      <td>0.980296</td>\n","      <td>0.980822</td>\n","      <td>[[184, 3], [1, 15]]</td>\n","      <td>0.200000</td>\n","      <td>0.062500</td>\n","    </tr>\n","    <tr>\n","      <th>39</th>\n","      <td>Week 43</td>\n","      <td>7506</td>\n","      <td>0.991087</td>\n","      <td>0.989305</td>\n","      <td>0.989761</td>\n","      <td>[[175, 2], [0, 10]]</td>\n","      <td>0.200000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>40</th>\n","      <td>Week 44</td>\n","      <td>7742</td>\n","      <td>0.987864</td>\n","      <td>0.985437</td>\n","      <td>0.986041</td>\n","      <td>[[188, 3], [0, 15]]</td>\n","      <td>0.200000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>41</th>\n","      <td>Week 45</td>\n","      <td>7861</td>\n","      <td>0.994625</td>\n","      <td>0.994595</td>\n","      <td>0.994443</td>\n","      <td>[[176, 0], [1, 8]]</td>\n","      <td>0.000000</td>\n","      <td>0.111111</td>\n","    </tr>\n","    <tr>\n","      <th>42</th>\n","      <td>Week 46</td>\n","      <td>8048</td>\n","      <td>0.990809</td>\n","      <td>0.989583</td>\n","      <td>0.989879</td>\n","      <td>[[175, 2], [0, 15]]</td>\n","      <td>0.133333</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>43</th>\n","      <td>Week 47</td>\n","      <td>8227</td>\n","      <td>0.995660</td>\n","      <td>0.994792</td>\n","      <td>0.995021</td>\n","      <td>[[186, 1], [0, 5]]</td>\n","      <td>0.200000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>44</th>\n","      <td>Week 48</td>\n","      <td>8354</td>\n","      <td>0.985415</td>\n","      <td>0.984848</td>\n","      <td>0.985057</td>\n","      <td>[[180, 2], [1, 15]]</td>\n","      <td>0.133333</td>\n","      <td>0.062500</td>\n","    </tr>\n","    <tr>\n","      <th>45</th>\n","      <td>Week 49</td>\n","      <td>8592</td>\n","      <td>0.989362</td>\n","      <td>0.989362</td>\n","      <td>0.989362</td>\n","      <td>[[178, 1], [1, 8]]</td>\n","      <td>0.125000</td>\n","      <td>0.111111</td>\n","    </tr>\n","    <tr>\n","      <th>46</th>\n","      <td>Week 50</td>\n","      <td>8721</td>\n","      <td>0.987013</td>\n","      <td>0.984848</td>\n","      <td>0.985368</td>\n","      <td>[[177, 3], [0, 18]]</td>\n","      <td>0.166667</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>47</th>\n","      <td>Week 51</td>\n","      <td>8977</td>\n","      <td>0.995195</td>\n","      <td>0.994595</td>\n","      <td>0.994746</td>\n","      <td>[[176, 1], [0, 8]]</td>\n","      <td>0.125000</td>\n","      <td>0.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9a8e1bd0-42c4-41c4-b16f-b360283b6af2')\"\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","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 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