Notebook_Pred2Town_XAI_v1.1.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Notebook_Pred2Town_XAI_v1.1.ipynb","provenance":[],"collapsed_sections":["f68zQYuvLgbx","ECNT_F17L4Po","KyDq0EFUL4P0","wxtPbs-7rEXc","O4-R4gWaL4QB","OJzj6kHML4QK","Bqv90P59L4QO","vR1E0Y_VL4QO","Y81ZknHZL4Qb","S4KYkAtyK_xA","5bWwUiHAK_yX","XCN5BkpIL4Qr","bR0gp988L4Qs","UYPF6KucL4RL","X1BuVY2EL4Rq"]},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.4"}},"cells":[{"cell_type":"markdown","metadata":{"id":"dNune3mALLPc"},"source":["# **Pred2Town - Version 1.1 - Git**"]},{"cell_type":"markdown","metadata":{"id":"U0nG-ByJ9YXl"},"source":["Note: The analyzes presented here are part of the research entitled \"Prediction of Homicides in Urban Centers: A Machine Learning Approach\", published in IntelliSys 2021. Git link: https://github.com/josesousaribeiro/Pred2Town.\n","\n","All the code components below, can be executed for a better understanding of the processes carried out in that research."]},{"cell_type":"markdown","metadata":{"id":"3Ue24WN3L4O7"},"source":["# **Analyzes**"]},{"cell_type":"markdown","metadata":{"id":"1qsYtxUtLPIe"},"source":["## - Libs:"]},{"cell_type":"code","metadata":{"id":"RqP5nGGULK3C","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613748740556,"user_tz":180,"elapsed":43151,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"f593b8e8-529a-4a1c-f1e7-3ee9fd6b41f5"},"source":["!pip install shap\n","!pip install eli5\n","!pip install lime\n","!pip install venn\n","!pip install scikit_posthocs\n","!pip install catboost\n","\n","\n","\n","from scipy.stats import friedmanchisquare\n","from sklearn.model_selection import train_test_split\n","from google.colab import files\n","from sklearn.ensemble import RandomForestClassifier\n","from sklearn.metrics import accuracy_score\n","from sklearn.metrics import precision_score\n","from sklearn.metrics import recall_score\n","from sklearn.metrics import plot_confusion_matrix\n","from sklearn.model_selection import cross_val_score\n","\n","from sklearn.linear_model import LogisticRegression\n","\n","from sklearn.model_selection import GridSearchCV\n","from sklearn.model_selection import StratifiedKFold\n","\n","\n","from folium.features import DivIcon\n","\n","from decimal import Decimal \n","\n","\n","from numpy import loadtxt\n","from xgboost import XGBClassifier\n","from sklearn.ensemble import GradientBoostingClassifier\n","from sklearn.tree import DecisionTreeClassifier \n","from matplotlib.pyplot import subplots\n","from venn import venn\n","from sklearn.neighbors import KNeighborsClassifier\n","from sklearn.naive_bayes import GaussianNB\n","from sklearn.neural_network import MLPClassifier\n","from sklearn import svm\n","\n","import seaborn as sns\n","import matplotlib.pyplot as plt\n","import shap\n","import eli5\n","import lime \n","import lime.lime_tabular \n","import pandas as pd\n","import csv\n","import io\n","import numpy as np\n","import seaborn as sns; sns.set()\n","import scikit_posthocs as sp\n","import pickle\n","import pandas as pd\n","import folium\n","\n","import math\n","import matplotlib.pyplot as plt\n","\n","import lightgbm as lgb\n","import catboost as cb\n","\n","\n","\n"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Collecting shap\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/44/20/54381999efe3000f70a7f68af79ba857cfa3f82278ab0e02e6ba1c06b002/shap-0.38.1.tar.gz (352kB)\n","\r\u001b[K     |█                               | 10kB 16.1MB/s eta 0:00:01\r\u001b[K     |█▉                              | 20kB 10.6MB/s eta 0:00:01\r\u001b[K     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The corresponding classes / functions should instead be imported from sklearn.feature_selection. Anything that cannot be imported from sklearn.feature_selection is now part of the private API.\n","pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n"],"name":"stderr"}]},{"cell_type":"markdown","metadata":{"id":"DXvvsfvGG4Xw"},"source":["## Global params to execution:"]},{"cell_type":"code","metadata":{"id":"EbuXJeGJK_NO","executionInfo":{"status":"ok","timestamp":1613750848214,"user_tz":180,"elapsed":1773,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}}},"source":["\n","name_dataset = 'dataset_pred2town_bel.csv'\n","name_target_class = 'Class'\n","\n","dt = {'info_gain_ent':[],\n","        'feat_imp_oob':[],\n","        'shap_rf':[],\n","        'shap_xgb':[],\n","        'shap_gb':[],\n","        'shap_dt':[],\n","        'eli5_rf':[],\n","        'eli5_xgb':[],\n","        'eli5_gb':[],\n","        'eli5_dt':[]}\n","\n","df_Pred2Town_feature_rank = pd.DataFrame(dt)\n","\n","\n","# If false, upload the templates to the google colab path in order to locate each model to be reused.\n","# If true, grid search will be performed and new best models will be located automatically.\n","run_grid_search_cb = False\n","run_grid_search_lgbm = False\n","run_grid_search_rf = False\n","run_grid_search_xgb = False\n","run_grid_search_gb = False\n","run_grid_search_lr = False\n","run_grid_search_dt = False\n","run_grid_search_knn = False\n","run_grid_search_nb = False\n","run_grid_search_nn = False\n","run_grid_search_svm = False\n","\n","\n","cv_grid_search = 7 \n","crossvalidation = 7\n","\n"],"execution_count":81,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"k_vqGO38L4PB"},"source":["## - Import dataset: dataset_pred2town_bel.csv\n"]},{"cell_type":"code","metadata":{"id":"w3RH4Su7Lxl0","colab":{"resources":{"http://localhost:8080/nbextensions/google.colab/files.js":{"data":"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","ok":true,"headers":[["content-type","application/javascript"]],"status":200,"status_text":""}},"base_uri":"https://localhost:8080/","height":70},"executionInfo":{"status":"ok","timestamp":1613748972909,"user_tz":180,"elapsed":16141,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"f47b37ef-c205-4e06-8545-80e4e1c94e81"},"source":["#please upload file dataset_pred2town_bel.csv \n","print(\"Note: upload file dataset_pred2town_bel.csv\")\n","uploaded1 = files.upload()\n","df = pd.read_csv(io.BytesIO(uploaded1[name_dataset]), encoding=\"UTF-8\", sep=\";\")"],"execution_count":9,"outputs":[{"output_type":"display_data","data":{"text/html":["\n","     <input type=\"file\" id=\"files-10d6f01f-0072-47bf-b780-f448bd4c5b0f\" name=\"files[]\" multiple disabled\n","        style=\"border:none\" />\n","     <output id=\"result-10d6f01f-0072-47bf-b780-f448bd4c5b0f\">\n","      Upload widget is only available when the cell has been executed in the\n","      current browser session. Please rerun this cell to enable.\n","      </output>\n","      <script src=\"/nbextensions/google.colab/files.js\"></script> "],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Saving dataset_pred2town_bel.csv to dataset_pred2town_bel (3).csv\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"KTwCguhjfmRv","colab":{"base_uri":"https://localhost:8080/","height":411},"executionInfo":{"status":"ok","timestamp":1613748980752,"user_tz":180,"elapsed":654,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"f2800a8b-54ec-476f-e50c-28a31f8a7eb3"},"source":["df"],"execution_count":10,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>mes_num_crb</th>\n","      <th>quant_lesao_corporal_crb</th>\n","      <th>quant_ameaca_crb</th>\n","      <th>quant_roubo_crb</th>\n","      <th>quant_injuria_crb</th>\n","      <th>quant_furto_crb</th>\n","      <th>quant_lesao_no_transito_crb</th>\n","      <th>quant_dano_no_transito_crb</th>\n","      <th>quant_difamacao_crb</th>\n","      <th>quant_homicidio_crb</th>\n","      <th>quant_abandono_do_lar_crb</th>\n","      <th>quant_conflitos_vicinais_crb</th>\n","      <th>quant_conflitos_conjugais_crb</th>\n","      <th>quant_fuga_do_lar_crb</th>\n","      <th>quant_estupro_de_vulneravel_crb</th>\n","      <th>quant_outros_fatos_atipicos_crb</th>\n","      <th>quant_roubo_de_veiculo_crb</th>\n","      <th>quant_estelionato_crb</th>\n","      <th>quant_dano_crb</th>\n","      <th>quant_dano_civil_crb</th>\n","      <th>quant_calunia_crb</th>\n","      <th>quant_conflitos_familiares_crb</th>\n","      <th>quant_trafico_de_drogas_crb</th>\n","      <th>quant_vias_de_fato_crb</th>\n","      <th>quant_apropriacao_indebita_crb</th>\n","      <th>quant_agressao_fisica_crb</th>\n","      <th>quant_receptacao_crb</th>\n","      <th>quant_estupro_crb</th>\n","      <th>quant_desaparecimento_de_pessoa_crb</th>\n","      <th>quant_tentativa_de_homicidio_crb</th>\n","      <th>quant_poluicao_sonora_crb</th>\n","      <th>quant_outras_fraudes_crb</th>\n","      <th>quant_desobediencia_crb</th>\n","      <th>quant_desacato_crb</th>\n","      <th>quant_perturbacoes_da_tranquilidade_crb</th>\n","      <th>Class</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1.0</td>\n","      <td>0.000000</td>\n","      <td>0.048193</td>\n","      <td>0.002433</td>\n","      <td>0.00000</td>\n","      <td>0.020619</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.071429</td>\n","      <td>0.1</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.011111</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.018868</td>\n","      <td>0.0000</td>\n","      <td>0.071429</td>\n","      <td>0.000000</td>\n","      <td>0.0000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.166667</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1.0</td>\n","      <td>0.081633</td>\n","      <td>0.084337</td>\n","      <td>0.124088</td>\n","      <td>0.03125</td>\n","      <td>0.036082</td>\n","      <td>0.233333</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.071429</td>\n","      <td>0.1</td>\n","      <td>0.222222</td>\n","      <td>0.142857</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.022222</td>\n","      <td>0.000000</td>\n","      <td>0.030303</td>\n","      <td>0.000000</td>\n","      <td>0.037736</td>\n","      <td>0.0625</td>\n","      <td>0.142857</td>\n","      <td>0.000000</td>\n","      <td>0.0625</td>\n","      <td>0.2</td>\n","      <td>0.111111</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>1.0</td>\n","      <td>0.000000</td>\n","      <td>0.132530</td>\n","      <td>0.063260</td>\n","      <td>0.03125</td>\n","      <td>0.018041</td>\n","      <td>0.066667</td>\n","      <td>0.027027</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.111111</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.030303</td>\n","      <td>0.000000</td>\n","      <td>0.018868</td>\n","      <td>0.0625</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0625</td>\n","      <td>0.1</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.2</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.166667</td>\n","      <td>0.0</td>\n","      <td>0.125</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1.0</td>\n","      <td>0.183673</td>\n","      <td>0.168675</td>\n","      <td>0.141119</td>\n","      <td>0.06250</td>\n","      <td>0.126289</td>\n","      <td>0.100000</td>\n","      <td>0.027027</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.2</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.066667</td>\n","      <td>0.000000</td>\n","      <td>0.030303</td>\n","      <td>0.000000</td>\n","      <td>0.056604</td>\n","      <td>0.1250</td>\n","      <td>0.142857</td>\n","      <td>0.083333</td>\n","      <td>0.1250</td>\n","      <td>0.3</td>\n","      <td>0.111111</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.4</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.166667</td>\n","      <td>0.4</td>\n","      <td>0.125</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1.0</td>\n","      <td>0.040816</td>\n","      <td>0.012048</td>\n","      <td>0.017032</td>\n","      <td>0.00000</td>\n","      <td>0.038660</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.058824</td>\n","      <td>0.000000</td>\n","      <td>0.0000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.2</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>1999</th>\n","      <td>12.0</td>\n","      <td>0.306122</td>\n","      <td>0.289157</td>\n","      <td>0.141119</td>\n","      <td>0.15625</td>\n","      <td>0.118557</td>\n","      <td>0.100000</td>\n","      <td>0.060811</td>\n","      <td>0.166667</td>\n","      <td>0.071429</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.142857</td>\n","      <td>0.0</td>\n","      <td>0.166667</td>\n","      <td>0.200000</td>\n","      <td>0.057143</td>\n","      <td>0.030303</td>\n","      <td>0.235294</td>\n","      <td>0.018868</td>\n","      <td>0.0625</td>\n","      <td>0.214286</td>\n","      <td>0.416667</td>\n","      <td>0.3750</td>\n","      <td>0.0</td>\n","      <td>0.111111</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.2</td>\n","      <td>0.2</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2000</th>\n","      <td>12.0</td>\n","      <td>0.183673</td>\n","      <td>0.277108</td>\n","      <td>0.192214</td>\n","      <td>0.28125</td>\n","      <td>0.381443</td>\n","      <td>0.366667</td>\n","      <td>0.506757</td>\n","      <td>0.222222</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.311111</td>\n","      <td>0.171429</td>\n","      <td>0.333333</td>\n","      <td>0.411765</td>\n","      <td>0.283019</td>\n","      <td>0.3750</td>\n","      <td>0.214286</td>\n","      <td>0.000000</td>\n","      <td>0.4375</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.166667</td>\n","      <td>0.0</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2001</th>\n","      <td>12.0</td>\n","      <td>0.040816</td>\n","      <td>0.012048</td>\n","      <td>0.043796</td>\n","      <td>0.00000</td>\n","      <td>0.015464</td>\n","      <td>0.000000</td>\n","      <td>0.047297</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.028571</td>\n","      <td>0.030303</td>\n","      <td>0.000000</td>\n","      <td>0.018868</td>\n","      <td>0.0000</td>\n","      <td>0.000000</td>\n","      <td>0.083333</td>\n","      <td>0.0000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2002</th>\n","      <td>12.0</td>\n","      <td>0.040816</td>\n","      <td>0.060241</td>\n","      <td>0.075426</td>\n","      <td>0.06250</td>\n","      <td>0.090206</td>\n","      <td>0.066667</td>\n","      <td>0.243243</td>\n","      <td>0.166667</td>\n","      <td>0.071429</td>\n","      <td>0.1</td>\n","      <td>0.000000</td>\n","      <td>0.142857</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.100000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.176471</td>\n","      <td>0.000000</td>\n","      <td>0.1875</td>\n","      <td>0.000000</td>\n","      <td>0.083333</td>\n","      <td>0.0000</td>\n","      <td>0.1</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2003</th>\n","      <td>12.0</td>\n","      <td>0.122449</td>\n","      <td>0.060241</td>\n","      <td>0.004866</td>\n","      <td>0.00000</td>\n","      <td>0.036082</td>\n","      <td>0.066667</td>\n","      <td>0.013514</td>\n","      <td>0.055556</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.022222</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.117647</td>\n","      <td>0.000000</td>\n","      <td>0.0000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0000</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.0</td>\n","      <td>0.111111</td>\n","      <td>0.0</td>\n","      <td>0.000000</td>\n","      <td>0.2</td>\n","      <td>0.000</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>2004 rows × 36 columns</p>\n","</div>"],"text/plain":["      mes_num_crb  ...  Class\n","0             1.0  ...      0\n","1             1.0  ...      1\n","2             1.0  ...      1\n","3             1.0  ...      0\n","4             1.0  ...      0\n","...           ...  ...    ...\n","1999         12.0  ...      0\n","2000         12.0  ...      0\n","2001         12.0  ...      0\n","2002         12.0  ...      0\n","2003         12.0  ...      0\n","\n","[2004 rows x 36 columns]"]},"metadata":{"tags":[]},"execution_count":10}]},{"cell_type":"markdown","metadata":{"id":"f68zQYuvLgbx"},"source":["\n","## - Split de Train/Test"]},{"cell_type":"code","metadata":{"id":"qC6JsqNUL4PC","executionInfo":{"status":"ok","timestamp":1613749008005,"user_tz":180,"elapsed":664,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}}},"source":["np.random.seed(0)\n","# Set target value and others features.\n","y_feature_name = name_target_class\n","\n","Y = (df[y_feature_name].astype(int))\n","\n","x_features_names = list(df.head(0))\n","x_features_names.remove(name_target_class)\n","X =  df[x_features_names]\n","\n","X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, stratify=Y) # 70% training and 30% tes\n","\n","\n"],"execution_count":11,"outputs":[]},{"cell_type":"code","metadata":{"id":"KUCYXQIXbPpV","colab":{"base_uri":"https://localhost:8080/","height":17},"executionInfo":{"status":"ok","timestamp":1613749016354,"user_tz":180,"elapsed":661,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"8167d335-b9c5-44f9-9587-b6ee07d28953"},"source":["X_train.to_csv(\"X_train.csv\")\n","files.download(\"X_train.csv\")\n","\n","X_test.to_csv(\"X_test.csv\")\n","files.download(\"X_test.csv\")\n","\n","y_train.to_csv(\"y_train.csv\")\n","files.download(\"y_train.csv\")\n","\n","y_test.to_csv(\"y_test.csv\")\n","files.download(\"y_test.csv\")\n","\n"],"execution_count":12,"outputs":[{"output_type":"display_data","data":{"application/javascript":["\n","    async function download(id, filename, size) {\n","      if (!google.colab.kernel.accessAllowed) {\n","        return;\n","      }\n","      const div = document.createElement('div');\n","      const label = document.createElement('label');\n","      label.textContent = `Downloading \"${filename}\": `;\n","      div.appendChild(label);\n","      const progress = 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// Send a message to notify the kernel that we're ready.\n","      channel.send({})\n","\n","      for await (const message of channel.messages) {\n","        // Send a message to notify the kernel that we're ready.\n","        channel.send({})\n","        if (message.buffers) {\n","          for (const buffer of message.buffers) {\n","            buffers.push(buffer);\n","            downloaded += buffer.byteLength;\n","            progress.value = downloaded;\n","          }\n","        }\n","      }\n","      const blob = new Blob(buffers, {type: 'application/binary'});\n","      const a = document.createElement('a');\n","      a.href = window.URL.createObjectURL(blob);\n","      a.download = filename;\n","      div.appendChild(a);\n","      a.click();\n","      div.remove();\n","    }\n","  "],"text/plain":["<IPython.core.display.Javascript object>"]},"metadata":{"tags":[]}},{"output_type":"display_data","data":{"application/javascript":["download(\"download_05d94a3e-6564-471d-b9a0-8411f5d0e7a2\", \"y_test.csv\", 3900)"],"text/plain":["<IPython.core.display.Javascript object>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"CZxCbpDTCWKf"},"source":["### Class stratification"]},{"cell_type":"code","metadata":{"id":"_JsPUN-Agz7J","colab":{"base_uri":"https://localhost:8080/","height":511},"executionInfo":{"status":"ok","timestamp":1613749025876,"user_tz":180,"elapsed":740,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"5e0a14e8-c417-4905-e3fd-528d66fa737d"},"source":["\n","title = 'Train count class'\n","labels = [0,1]\n","sizesTrain = [y_train.to_list().count(0), y_train.to_list().count(1)]\n","fig1, ax1 = plt.subplots()\n","ax1.pie(sizesTrain, labels=labels, autopct='%1.1f%%', shadow=True, startangle=90)\n","plt.title(title)\n","plt.show()\n","\n","title = 'Test count class'\n","labels = [0,1]\n","sizesTest = [y_test.to_list().count(0), y_test.to_list().count(1)]\n","fig1, ax1 = plt.subplots()\n","ax1.pie(sizesTest, labels=labels, autopct='%1.1f%%', shadow=True, startangle=90)\n","plt.title(title)\n","plt.show()"],"execution_count":13,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"B3TCAdqPpl1I","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613749032036,"user_tz":180,"elapsed":644,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"27f614ff-3802-4350-da03-75a4b43f8a9b"},"source":["print(df[y_feature_name].to_list().count(0))\n","print(df[y_feature_name].to_list().count(1))"],"execution_count":14,"outputs":[{"output_type":"stream","text":["970\n","1034\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"44tbaCMWL4PH"},"source":["## - Train, test and algorithm analysis"]},{"cell_type":"markdown","metadata":{"id":"NZcbBXBXSuBf"},"source":["### LightGBM - Create a GridSearch to identify the best classify"]},{"cell_type":"code","metadata":{"id":"UBOA1LBXSuBh","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750417181,"user_tz":180,"elapsed":1029,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"fbe4d2e5-e0d6-4245-df36-dfeef41a5943"},"source":["filename = 'best_model_lgbm.sav'\n","\n","if run_grid_search_lgbm == True:\n","  # Create the parameter grid\n","  # https://lightgbm.readthedocs.io/en/latest/Parameters.html\n","  param_grid = {\n","          'learning_rate': [0.1, 0.5],\n","          'max_depth': [1, 6, 12],\n","          'bootstrap': [True, False],\n","          'n_estimators': [10, 100, 200],\n","\t\t      'min_data_in_leaf': [1, 10, 20, 40],\n","          'boosting_type': ['gbdt','dart','goss','rf'],\n","          'num_leaves': [31,100,200]\n","          }\n","  \n","  model_lgbm = lgb.LGBMClassifier(objective='binary')\n","\n","  grid_search = GridSearchCV(estimator=model_lgbm, \n","                             param_grid=param_grid,  \n","                             cv=StratifiedKFold(cv_grid_search), \n","                             n_jobs = 3, verbose = 2,\n","                             scoring = 'roc_auc')\n","  \n","  \n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_lgbm = grid_search.best_estimator_\n","  \n","  #save\n","  pickle.dump(model_lgbm, open(filename, 'wb'))\n","  files.download(filename)\n","else: \n","  model_lgbm = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_lgbm)\n","y_pred_lgbm = model_lgbm.predict(X_test)\n","\n"],"execution_count":32,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","LGBMClassifier(boosting_type='goss', bootstrap=True, class_weight=None,\n","               colsample_bytree=1.0, importance_type='split', learning_rate=0.1,\n","               max_depth=1, min_child_samples=20, min_child_weight=0.001,\n","               min_data_in_leaf=40, min_split_gain=0.0, n_estimators=100,\n","               n_jobs=-1, num_leaves=31, objective='binary', random_state=None,\n","               reg_alpha=0.0, reg_lambda=0.0, silent=True, subsample=1.0,\n","               subsample_for_bin=200000, subsample_freq=0)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"Dwvy6QpKSuBj"},"source":["LGBM - Accuracy, precision and Recall."]},{"cell_type":"code","metadata":{"id":"Ftx8xsP7SuBj","colab":{"base_uri":"https://localhost:8080/","height":76},"executionInfo":{"status":"ok","timestamp":1613750417182,"user_tz":180,"elapsed":1007,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"46b316a8-c74f-4e0f-deac-b5ff9bd6034f"},"source":["y_pred = y_pred_lgbm\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys\n","\n"],"execution_count":33,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.754153</td>\n","      <td>0.768977</td>\n","      <td>0.749196</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.754153   0.768977  0.749196"]},"metadata":{"tags":[]},"execution_count":33}]},{"cell_type":"markdown","metadata":{"id":"up1TIwrVSuBl"},"source":["LGBM - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"ssixUBzgSuBm","colab":{"base_uri":"https://localhost:8080/","height":285},"executionInfo":{"status":"ok","timestamp":1613750417819,"user_tz":180,"elapsed":1634,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"3e87d208-5c97-4820-e2fa-acb01945850b"},"source":["plot_confusion_matrix(model_lgbm, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":34,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"xU9PjCBfSuBn"},"source":["**LGBM** - Statistical analisys"]},{"cell_type":"code","metadata":{"id":"DNmY9dyvSuBo","colab":{"base_uri":"https://localhost:8080/","height":305},"executionInfo":{"status":"ok","timestamp":1613750418351,"user_tz":180,"elapsed":2154,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"a03d5ba6-48d9-4601-b4c5-667217fc6b47"},"source":["#del dataframe_analisys\n","hit_rates = cross_val_score(model_lgbm, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_lgbm = hit_rates"],"execution_count":35,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"gSdYS22YawLB"},"source":["### CatBoost - Create a GridSearch to identify the best classify"]},{"cell_type":"code","metadata":{"id":"4VrBqiTKawLD","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750428448,"user_tz":180,"elapsed":733,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"5551fbe8-4bb1-4670-d547-dce73dab5981"},"source":["filename = 'best_model_cb.sav'\n","\n","if run_grid_search_cb == True:\n"," #parameters\n"," #https://catboost.ai/docs/concepts/parameter-tuning.html\n","  param_grid = {\n","            'learning_rate':[0.1, 0.5], \n","            'depth':[1, 6, 12],\n","            'iterations':[10, 100, 200],\n","            'grow_policy':['SymmetricTree','Depthwise','Lossguide'],\n","            'bagging_temperature': [0,0.5,1]\n","           }\n","  model_cb =  cb.CatBoostClassifier()\n","\n","  grid_search = GridSearchCV(estimator=model_cb, \n","                             param_grid=param_grid,  \n","                             cv=StratifiedKFold(cv_grid_search), \n","                             n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","  \n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_cb = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_cb, open(filename, 'wb'))\n","  files.download(filename)\n","else: \n","  model_cb = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_cb)\n","y_pred_cb = model_cb.predict(X_test)\n","\n","#Fitting 10 folds for each of 648 candidates, totalling 6480 fit"],"execution_count":36,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","<catboost.core.CatBoostClassifier object at 0x7f495d763748>\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"sMWK_gwqawLF"},"source":["CatBoost - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"sIU64PohawLG","colab":{"base_uri":"https://localhost:8080/","height":76},"executionInfo":{"status":"ok","timestamp":1613750428449,"user_tz":180,"elapsed":716,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"36f19a2e-08ea-46d6-94cf-38e6941cc1ed"},"source":["y_pred = y_pred_cb\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys\n","\n"],"execution_count":37,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.737542</td>\n","      <td>0.747573</td>\n","      <td>0.742765</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.737542   0.747573  0.742765"]},"metadata":{"tags":[]},"execution_count":37}]},{"cell_type":"markdown","metadata":{"id":"ZNo9hZKkawLI"},"source":["CatBoost - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"IavklS8eawLI","colab":{"base_uri":"https://localhost:8080/","height":285},"executionInfo":{"status":"ok","timestamp":1613750428768,"user_tz":180,"elapsed":1029,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"91f2879e-48bf-4bd6-bb74-cfb53f01130b"},"source":["plot_confusion_matrix(model_cb, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":38,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"YYY0b8nnawLK"},"source":["CatBoost - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"tT4ky0KgawLK","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750513983,"user_tz":180,"elapsed":86239,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"86f4f337-459f-4135-b3b7-72a2d874e103"},"source":["#del dataframe_analisys\n","hit_rates = cross_val_score(model_cb, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_cb = hit_rates"],"execution_count":39,"outputs":[{"output_type":"stream","text":["0:\tlearn: 0.6478543\ttotal: 143ms\tremaining: 28.5s\n","1:\tlearn: 0.6055721\ttotal: 202ms\tremaining: 20s\n","2:\tlearn: 0.5714269\ttotal: 255ms\tremaining: 16.8s\n","3:\tlearn: 0.5464725\ttotal: 314ms\tremaining: 15.4s\n","4:\tlearn: 0.5173811\ttotal: 373ms\tremaining: 14.5s\n","5:\tlearn: 0.4978077\ttotal: 427ms\tremaining: 13.8s\n","6:\tlearn: 0.4762658\ttotal: 482ms\tremaining: 13.3s\n","7:\tlearn: 0.4581493\ttotal: 543ms\tremaining: 13s\n","8:\tlearn: 0.4426409\ttotal: 601ms\tremaining: 12.8s\n","9:\tlearn: 0.4225456\ttotal: 679ms\tremaining: 12.9s\n","10:\tlearn: 0.4107139\ttotal: 733ms\tremaining: 12.6s\n","11:\tlearn: 0.3960987\ttotal: 787ms\tremaining: 12.3s\n","12:\tlearn: 0.3826959\ttotal: 843ms\tremaining: 12.1s\n","13:\tlearn: 0.3641639\ttotal: 903ms\tremaining: 12s\n","14:\tlearn: 0.3541082\ttotal: 956ms\tremaining: 11.8s\n","15:\tlearn: 0.3489836\ttotal: 962ms\tremaining: 11.1s\n","16:\tlearn: 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14.4s\tremaining: 1s\n","187:\tlearn: 0.0268807\ttotal: 14.5s\tremaining: 924ms\n","188:\tlearn: 0.0267484\ttotal: 14.5s\tremaining: 846ms\n","189:\tlearn: 0.0265253\ttotal: 14.6s\tremaining: 768ms\n","190:\tlearn: 0.0263308\ttotal: 14.6s\tremaining: 690ms\n","191:\tlearn: 0.0261963\ttotal: 14.7s\tremaining: 613ms\n","192:\tlearn: 0.0259752\ttotal: 14.8s\tremaining: 536ms\n","193:\tlearn: 0.0257500\ttotal: 14.8s\tremaining: 458ms\n","194:\tlearn: 0.0255689\ttotal: 14.9s\tremaining: 382ms\n","195:\tlearn: 0.0253433\ttotal: 14.9s\tremaining: 305ms\n","196:\tlearn: 0.0250944\ttotal: 15s\tremaining: 228ms\n","197:\tlearn: 0.0248602\ttotal: 15s\tremaining: 152ms\n","198:\tlearn: 0.0247309\ttotal: 15.1s\tremaining: 75.9ms\n","199:\tlearn: 0.0245927\ttotal: 15.2s\tremaining: 0us\n"],"name":"stdout"},{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYUAAAD7CAYAAACFfIhNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3dd1xT5/4H8E8ShowwBQzgqBv3oK66ilpREbXO2np/1Wrrta3+7K2j1lVtey+OetU66s/Wal24GW5ERa2j9ooWBzgQRIbIqGCUkZzfH96eNoYRIOQE+LxfL18veM45Od8nkXySM55HJgiCACIiIgByqQsgIiLzwVAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQWUhdgDFlZT6HVmv/tFq6u9sjIyJW6DKOoTn0B2B9zx/4Yl1wug7OzXZHLqkUoaLVClQgFAFWmTkNUp74A7I+5Y39Mg4ePiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiETV4j4FMm/ff/8T0tKyyrWth4cz3ntvnJErIqLiMBSo0qWlZcHbu2+5tk1KijByNURUEh4+IiIiEUOBiIhEDAUiIhIxFIiISMRQICIiEUOBiIhEDAUiIhIxFIiISMRQICIiEUOBiIhEDAUiIhIxFIiISMRQICIiEUOBiIhEDAUiIhIxFIiISMRQICIiEUOBiIhEDAUiIhIxFIiISMRQICIiEUOBiIhEDAUiIhIxFIiISMRQICIiEUOBiIhEDAUiIhKZPBS+/fZbNGvWDHFxcQCA6OhoBAYGon///pgwYQIyMjJMXRIREf2XSUPh+vXriI6OhpeXFwBAq9VixowZmD9/Po4ePQpfX18sW7bMlCUREdFfmCwU8vPzsWjRIixcuFBsi4mJgbW1NXx9fQEAY8aMwZEjR0xVEhERvcRkobBy5UoEBgbC29tbbEtJSYGnp6f4u4uLC7RaLbKzs01VFhER/YWFKXZy5coVxMTE4NNPP62Ux3d1ta+Ux60Mbm5KqUswGkP7YmtrBaWyVrn2YWtrZbLnrDq9NgD7Y+7MtT8mCYVffvkFd+/eRZ8+fQAAqampeO+99zBu3DgkJyeL62VmZkIul8PJyalMj5+RkQutVjBqzZXBzU2J9PQcqcswirL0Ra3OR07O83LtR63ON8lzVp1eG4D9MXdS90culxX7Ydokh4/ef/99nD17FpGRkYiMjESdOnXw/fffY+LEiXj+/DkuX74MANi5cyf8/f1NURIRERXBJN8UiiOXy7FkyRIsWLAAeXl58PLywtKlS6UsiYioRpMkFCIjI8WfO3TogLCwMCnKICKil/COZiIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiKRhal2NGXKFCQlJUEul8PW1hbz5s2Dj48P4uPjMXv2bGRnZ8PJyQlBQUFo0KCBqcoiIqK/MFkoBAUFQalUAgAiIiIwZ84c7N+/HwsWLMDYsWMxZMgQhISEYP78+diyZYupyiIior8w2eGjPwIBAHJzcyGTyZCRkYEbN24gICAAABAQEIAbN24gMzPTVGUREdFfmOybAgB8/vnnOHfuHARBwMaNG5GSkgIPDw8oFAoAgEKhgLu7O1JSUuDi4mLw47q62ldWyUbn5qYsfaUqwtC+2NpaQamsVa592Npamew5q06vDcD+mDtz7Y9JQ+Grr74CABw4cABLlizBtGnTjPK4GRm50GoFozxWZXJzUyI9PUfqMoyiLH1Rq/ORk/O8XPtRq/NN8pxVp9cGYH/MndT9kctlxX6YluTqo6FDh+LixYuoU6cO0tLSoNFoAAAajQaPHj2CSqWSoiwiohrP4FCIiIhAYWFhuXby9OlTpKSkiL9HRkbC0dERrq6u8PHxQXh4OAAgPDwcPj4+ZTp0RERExmPw4aNVq1Zh7ty5GDhwIIYMGYK2bdsavJNnz55h2rRpePbsGeRyORwdHbF+/XrIZDIsXLgQs2fPxtq1a+Hg4ICgoKBydYSIiCrO4FAIDQ3FrVu3EBISgo8//hg2NjYYMmQIAgMD4e3tXeK2tWvXxq5du4pc1qhRI+zevbtsVRMRUaUo0zmF5s2bY9asWTh9+jQWLFiAI0eOoF+/fnj77bcRGhoKrVZbWXUSEZEJlPnqo8TERISGhiI0NBQymQxTp06FSqXCtm3bcOzYMXz77beVUScREZmAwaGwbds2hISEICEhAQMGDMCSJUvQrl07cXn//v3RrVu3SimSiIhMw+BQiIqKwvjx49GnTx9YWVnpLbexscHq1auNWhwREZmWwecUOnXqhAEDBugFwqZNm8Sfu3fvbrzKiIjI5AwOhTVr1hTZvm7dOqMVQ0RE0ir18NH58+cBvLjb+MKFCxCEP4eTSEpKgp2dXeVVR0REJlVqKHz++ecAgPz8fMyZM0dsl8lkcHNzw9y5cyuvOiIiMqlSQyEyMhIAMHPmTCxZsqTSCyIiIukYfE6BgUBEVP2V+E1hwIABOHz4MACgV69ekMlkRa536tQpoxdGRESmV2IoLF68WPx56dKllV4MERFJq8RQ8PX1FX/u1KlTpRdDRETSMvicwqZNm3Dz5k0AQHR0NHr37g0/Pz9cuXKl0oojIiLTMjgUfvzxR3GI7OXLl+Pdd9/F3//+d3z99deVVhwREZmWwaGQk5MDpVKJ3NxcxMbGYty4cRg5ciTi4+Mrsz4iIjIhgwfEU6lU+M9//oM7d+7A19cXCoUCubm5UCgUlVkfERGZkMGhMHPmTEydOhVWVlZYtWoVAODkyZNo3bp1pRVHRESmZXAo9OrVC2fPntVp8/f3h7+/v9GLIiIiaZRp5rWcnBzEx8fj6dOnOu1du3Y1alFERCQNg0Nh3759WLRoEWxtbVGrVi2xXSaT4cSJE5VSHBERmZbBobBixQqsXLkSvXr1qsx6iIhIQgaHgkaj4cxqVOV8//1PSEvLKnU9W1srqNX5Om337t1Gw4ZNyr1vKbdv3FiFUaNGlnvfhj5vxfHwcMZ7740r9/YkHYNDYdKkSVi3bh2mTJkCudzg2xuIJJWWlgVv776lrqdU1kJOznOdtnPnfkHPnqVvWxwpt09Ojir3fgHDn7fiJCVFVGj/JB2DQ+HHH3/E48ePsXHjRjg5Oeks4yipRETVg8GhwFFSiYiqP4NDgaOkEhFVfwafHMjPz8eKFSvQp08fdOzYEQBw9uxZbN26tdKKIyIi0zI4FL7++mvExcVh2bJl4gxsTZo0wY4dOyqtOCIiMi2DDx9FRETg2LFjsLW1Fa8+8vDwQFpaWqUVR0REpmXwNwVLS0toNBqdtszMTL0rkYiIqOoyOBT8/f0xa9YsPHjwAADw6NEjLFq0CIMGDaq04oiIyLQMDoXp06ejbt26CAwMxJMnT9C/f3+4ubnhww8/rMz6iIjIhAw+p5CYmIhXXnkFH3zwATQaDfr27YtmzZpVZm1ERGRipYaCIAiYM2cODhw4gDp16sDd3R1paWlYs2YNhgwZgq+//lq8Gqk4WVlZmDlzJhITE2FlZYX69etj0aJFcHFxQXR0NObPn4+8vDx4eXlh6dKlcHV1NVoHiYjIcKUePgoODsalS5cQHByMkydPIjg4GKdOncLOnTtx+fJl7Ny5s9SdyGQyTJw4EUePHkVYWBjq1q2LZcuWQavVYsaMGZg/fz6OHj0KX19fLFu2zCgdIyKisis1FEJCQjB37ly0adNGp71NmzaYM2cOQkJCSt2Jk5MTOnfuLP7erl07JCcnIyYmBtbW1vD19QUAjBkzBkeOHClrH4iIyEhKDYW7d+/i1VdfLXLZq6++irt375Zph1qtFjt27ICfnx9SUlLg6ekpLnNxcYFWq0V2dnaZHpOIiIyj1HMKGo0G9vb2RS6zt7eHVqst0w4XL14MW1tbvPPOOzh+/HiZti2Oq2vR9ZkjNzel1CUYjaF9sbW1glJZq/QVi9m2Is9ZWfb98nqWlopy1y319pmZFfu/VpHX7I/tjf1/vTr97QDm259SQ6GwsBAXLlyAIAhFLn/5hraSBAUFISEhAevXr4dcLodKpUJycrK4PDMzE3K5vMw3xGVk5EKrLbo+c+LmpkR6eo7UZRhFWfqiVufrzVVgKLU6v0LPmaH7Lmo+hYICjUHb5ubm4/ff85GTk4+cnAIUFr74oPTwoRtOn06Eg4MVHBys4OxsDUtLhcG1G7r/4pjieStpe2P+X69OfzuA9P2Ry2XFfpguNRRcXV0xZ86cYpe7uLgYVMQ333yDmJgYbNiwAVZWVgCAVq1a4fnz57h8+TJ8fX2xc+dO+Pv7G/R4RFJ49qwQ9+79jvj4J0hOzkVy8lPk5hYUs3ZjJCTEir/J5YCHhx3q1rVH/foOaN7cGY6O1qYpnMhApYZCZGRkhXdy+/ZtfPfdd2jQoAHGjBkDAPD29saaNWuwZMkSLFiwQOeSVCJzIQgC0tLUuHbtMW7ezEJSUg6K+dJcKq0WSEl5ipSUp7h06cWYYfXqKdGqlSt8fT3g4GBlxMqJysfgm9cqokmTJoiNjS1yWYcOHRAWFmaKMogMlpX1HA8f1sWSJb8iPf1Zpe0nMTEHiYk5OHIkAa1aueK111Ro2NCx1Ht/iCqLSUKBqCooLNQiJiYDly6l4vbtbAhCfQClB4KFhRyurrXg4GAFpdISVlYvzhvcvRsNlaoVnjzJR3Z2HrKz84p9DK1WwLVrj3Ht2mPUr69E//71y/2NhKgiGApU4/3+ex4iIh4gKioJanVhqet7eNiiSRMnNGjgAE9PO9SubQO5XP+TfXDwHowePVL8Xa0uQFJSLu7ff4KbNzPx4EFukY+fkJCDDRtioFS2RmJiDurVM8+rVKh6YihQjfXgQQ6ioh7i6tXHJV69plDI0KSJE1q3rg0fH5dyH/u3tbVE06bOaNrUGW+8UR+//56Ha9ce4/z5FDx6pP+NJCfHEatXR6NTpzoYOLAB7Owsy7VforJgKFCNIggCYmOzcOLEA8THPylxXVvbHPj7t0f79m6wsTH+n4qjozV69PBC9+6euHv3d5w+/RA3b2a+VC9w8WIqfvvtMQYPbghfX3eeb6BKxVCgGkGrFRATk4ETJx7g4cOiD9sAgI2NBTp2dEenTnVw5swqdOs2sNJrk8lkaNzYCY0bO/33pPN9xMXp3tWvVhciODgOMTGPMWJEEyiVvFKJKgdDgao1jQa4fDkNkZEPijxE8wcPD1u89ponOnZ0h7W14TeYGVu9ekq8/35rxMVlYcuWS3j+3FZn+fXrmbh//1eMHNkErVrVlqhKqs4YClQtFRZqsWtXHDZvtsKTJ3HFrtekiRN69vSCr68KT58Wf3WQqTVt6oyWLa/Aw+NtHD+eiIKCP4eTefq0ED/+eBM9enhi0KBXYGFh8FxZRKViKFC1otFosXfvHSxf/ut/zxnoH3+XyYBWrVzRp09deHu/uLKnqKuHpCaXC/Dzq4vWrWtj585YJCToDotw5kwy7t/PwbhxzeHiUv5xioj+iqFA1YJWKyAk5C6WLv0Vd+4UPcquXA60b++O11/3Rp06diausPzc3GwwZUpbnDqVhGPHEqDR/Hml1IMHOfj3v6/gb3/zQePGZRszjKgoDAWq0rRaAQcPxmPp0su4dSuryHUUChk6dfJA79514epaNT9RKxQy9OlTF02aOOGnn24iK+vPQ11qdSE2bIjBsGGN0LWrSsIqqTpgKFCVFRWVhEWLLuLatcdFLrewkKN58wIMGdIFzs5VMwxeVq+eEtOnt8eOHXE6l69qtQL27r2D1NSnCAxsJGGFVNXxDBVVOdevZ2DMmEMYMeJgkYGgUMjw1lvNcP78aPTtW1htAuEPtraWGD++Bfr3r6+37Ny5FGzcGINnlTdcE1Vz/KZAVUZSUg6Cgi5j1664IscFksmA4cOb4NNPO6JhQ0fTF2hCcrkM/frVQ506tti+PVbn6qTbt7OxZQswblyOeCKdyFD8pkBmLzc3H4sXX0TXrsEIDi46EAIDG+LMmVFYu9av2gfCX7VuXRsffdQWTk668zJkZMgwcOAB3LiRIVFlVFUxFMhsCYKAW7fk6NYtGKtXRyMvT3+Wv27dVDhyZBg2buyHpk2dJahSel5e9pg2rR0aNHDQaU9NVWPw4FCcO5dczJZE+hgKZJaSk59i7dprOHLEEqmpar3lzZs7Y9s2f+zfPxgdOrhLUKF5USqt8MEHrdG6tatOe05OPkaPPojQ0LsSVUZVDc8pkFnJy9Pg6NEEnDnzsMjDRHXq2GL27FcxenRTKBT8TPNXlpZyjBvng5CQuzh3LkVsz8/XYtKkCDx69AwTJ7aSsEKqChgKZDZu387C7t13kJmpP2G8paUcU6a0wbRpHWBvzyGkiyOXyzB0aCNYWibj1Kk/79IWBGDOnHNIS3uKOXM6caRVKhZDgST37FkhwsPjcfFiapHL+/Spiy+/7IZGjXjHriFkMhm6dQOGD38d06efRmHhn1cmrVwZjezsfAQFdTfLoT1IegwFklRcXBZ27ozDkyf5esucnKzRs2cu/u//BvCTbTmMHt0Ubm61MGHCcZ0Z5TZvvoGcnHysXt0blpbSjQhL5okHZUkShYVahIfHY8OGGL1AkMmA7t09MWNGRzRsqGUgVICfXz3s3z9Yb8C8ffvuYMKE43j+vPTpR6lmYSiQyaWnq/Htt1dx6lSS3rIXg7+1wdChjSSd16A6ad/eHSEhgahTR3duhqNHEzB27GHk5up/S6Oai6FAJnX5chpWrLiCpCTd2c9kMsDPzxuffNIBr7xSc24+M5VmzZwRFjYE9evr3stw9mwyhg8PL/LkPtVMDAUyCY1Gi/3772Dnzjjk52t1ljk6WmHy5NYYOPAVWFryv2RlqV/fAeHhgWjeXPcmvytX0jF0aChSU59KVBmZE/4FUqVTq4HvvvtN59r5P7Ru7Yp//KMDrywyEQ8POxw4EKh3w9+tW1kYPDgUCQlPJKqMzAVDgSpVdHQ6tm+3wr17um82FhZyjBjRGH/7mw9sbXnfgSm5uNTCnj2D0L27p057QsITDB4cgtjYoueloJqBoUCVZv/+Oxg8OAS5ubpXDzk7W+Pjj9uiSxcVryySiL29FbZvH6A3/HZqqhpDhoQiLY2vS03FUCCjEwQBq1dH44MPTugNYteokSP+93/bw8vLXqLq6A+1alnghx/6YfjwxjrtmZnPsWePZbHTmlL1xlAgo9JotPjss3NYvPii3rKePb3w/vutYWfHw0XmwtJSgTVr/PDuuy102gsKZNi4MQYxMRx6u6ZhKJDRqNUFGD/+OH744bpOu1wuYMyYpggMbAiFgoclzI1cLkNQUHdMm9ZOp72wUMCWLTfwyy9pElVGUmAokFFkZ+dhxIiDOHLkvk67UmmFoUML4OvrIU1hZBCZTIbPP++M+fM767RrtUBwcByioh5KVBmZGkOBKiw9/RmGDQvD5cu6nyhVKjuEhQWiXr0ixsAms/TRR+2wYkUvyGS6r1lo6D0cPnwfQlHjmVO1wlCgCklJeYqhQ0Nx/brusWcfHxccPjwULVq4FrMlmau3326OQYMK9Q71nTjxAPv23YFWy2CozhgKVG6JiTkIDAzF7du6V6l06VIHYWGB8PTkFUZVVePGWrz3XktYWem+RZw/n4rt22/pDMdN1QtDgcolLi4TgYEhenfA9u7tjZ07B8LBwbqYLamqaNrUGZMnt4Gtre4I+9HRj7Fp040i58ymqs8koRAUFAQ/Pz80a9YMcXFxYnt8fDxGjx6N/v37Y/To0bh//74pyqEKio//Ha+/vgvJybpj5fj7N8BPP/nzDuVqpF49JT78sC0cHa102mNjs7Bhw29Qqwskqowqi0lCoU+fPti2bRu8vLx02hcsWICxY8fi6NGjGDt2LObPn2+KcqgCHjzIwfDh4UhO1h3l9M03G+P77/tyuOtqyMPDFh9+2BZubjY67QkJOVi79lqREyRR1WWSUPD19YVKpdJpy8jIwI0bNxAQEAAACAgIwI0bN5CZmWmKkqgcUlKeYvjwcL1hr8eObYY1a17nLF7VmItLLUyZ0gZeXnY67ampL+bGSE9XS1QZGZtk5xRSUlLg4eEBheLFG4lCoYC7uztSUvRH0iTppac/w4gR4bh/X/ccwqhRTfHNN72gUPD0VHWnVFph8uQ2aNhQd06GzMznWL36KkdYrSaqxRzNrq5V5yoXNzel1CWUWUbGM4wZc0jvKqNRo5ph27ZBsLAoORBsba2gVNYqcZ2Stq3Ic1aWfb+8nqWlotx1S719ZmbF/q8V97wplcD06b7YuPE3XL2aLrar1YVYv/43TJrUGm3bulf4dStKVfzbKYm59keyUFCpVEhLS4NGo4FCoYBGo8GjR4/0DjMZIiMjt0pcO+3mpkR6eo7UZZTJ77/nYcSIcPz222Od9iFDGmPFih7Iyip9Yha1Oh85OeWb2Uutzq/Qc2bovpXKWnrrFRRoyl23OWxfmc/b2LHNYGUl1xkCo6BAi3XrrmLYsMaoV69ir9vLquLfTkmk7o9cLiv2w7Rk3/ldXV3h4+OD8PBwAEB4eDh8fHzg4uIiVUn0ktzcfLz11mFcvaobCH5+dREcHMBzCDWYQiHDqFFN0LdvXZ12QQD27buDn39W8O7nKsokofDll1+iZ8+eSE1Nxfjx4zFo0CAAwMKFC7F161b0798fW7duxRdffGGKcsgAanUB3nnniN7QFd27e2LTpjdgbV0tjjxSBchkMvj7N8CIEY3x8rQYly5ZYOrUUygo4L0MVY1J/rLnzp2LuXPn6rU3atQIu3fvNkUJVAbPnxfi3XeP4eefdU/6d+pUB1u2+MPGhoFAf+rSRQWl0gpbt95CQcGfdzoHB8chLU2NH37oB3t7qxIegcwJLxkhHfn5GkyaFIFTp5J02tu3d8P27f6wt+eNaaSvZUtXTJ7cGnZ2uh8YTp1KwuDBoXj4MLeYLcncMBRIVFioxeTJJ3D0aIJOe8uWrhy6gkpVv74DPvqoHVxdda9aun49A/7++3WuViLzxVAgAC9mTPv445MID4/XaW/WzBm7dw+Cs3P5L62kmsPNzQYffdQWHh66A+alpakRGBiK8PB7ElVGhmIoELRaAZ9+egZ7997RaX/lFQfs2TMItWvbFLMlkT6l0gojRhTA37+BTvuzZ4WYMOE4Vq+O5pVJZoyhUMMJgoA5c85h27ZbOu316imxb99geHjYFbMlUfEsLYFNm/phypQ2essWL76I6dNPIz+fVyaZI4ZCDSYIAhYsuKA3p7JKZYe9ewPg5VV17hQn86NQyLFwYVcsX95T76737dtjMWbMIWRn50lUHRWHoVBDCYKAxYsvYv36azrtbm422LcvAPXrOxSzJVHZjBvng507B8DBQfey1LNnkzFgwH7cvZtdzJYkBYZCDSQIAv71r1/w7bdXddpdXGphz54ANGrkJFFlVF317OmNw4eH6n3YuHv3d7zxxn5ERCRKVBm9jKFQAy1b9itWrLii0+bkZI3duwfBx4fDjFDlaNLEGUeODEXnznV02nNy8vH224excuUVnoA2AwyFGmbFiv9g6dJfddocHa2wZ88gtG5dW6KqqKZwdbXBnj0BGDWqqU67IABffXUJEydGIDeXs7lJiaFQg6xaFY1//vMXnTal0gq7dg1CmzZuElVFNY21tQKrV/fG4sVdoVDoDpoUFnYPgwYd0Ju3g0yHoVBDrF4djS+/vKjTZm9vieDggWjf3l2iqqimkslk+OCDNggOHghnZ9075W/ezMQbb+zDiRM8zyAFhkI198dJ5cWLdQPB1tYCO3YMhK+vh0SVEb04AX3s2Jto0UL3XFZ2dh7eeuswvvrqIgoLtcVsTZWBoVCNCYKAefN+xjff/Een/UUgDNA74Uckhfr1HXDw4FAMGdJQb9nKldEYPjwcyckcUM9UGArVlEajxSefRGHDhhiddjs7S2zfPgBdu3pKVBmRPjs7S2zY0Bdz53aGXK57nuH8+RS0a7dZb+ReqhwMhWooL0+Dv/89Um/oCicna+zZMwjdujEQyPzIZDJMndoO+/cHwMPDVmdZevozjB59EEFBv0Cj4eGkysRQqGays/MwevRBHDhwV6e9dm0b7N8/GB078hwCmbeuXT0RGTkCPXt66bQLArB8+X8wbFgYEhOrz3zN5oahUI3cv/8EAwce0JsxzcvLHmFhgWjZ0lWiyojKxs3NBsHBAzFzpq/eVJ8XLqSid+/d2Lkzlje7VQKGQjXx669pGDhwP+7c0R1HpmFDR4SGBnLoCqpyFAo5Pv20I3bvHgR3d93DSbm5BZg69RTee+84MjOfS1Rh9cRQqAZCQ+9i2LAwPH6s+8fRuXMdHDo0FHXrKiWqjKjievb0RnT03+DnV1dvWXh4PHr23M3Je4yIoVCFFRZq8cUXFzBxYgSeP9cdm/7NNxtj9+5BcHHhjGlU9alU9tixYwD++c/XYGOjOw/0o0dqTJhwHOPHH0Na2lOJKqw+GApVVHr6M4wadRBr1lzVWzZ9enusXeuHWrUsitiSqGqSyWR4771WiIh4E23b6o/TdfBgPF57bRe2br3Jcw0VwFCogk6efIDXX9+Ds2eTddotLeVYsaIXPvusk9613kTVRZMmzjh0aCj+8Y8OepP3PHmSj08+iUJgYCiuXUuXqMKqjaFQheTlaTBv3s8YPfoQHj1S6yxTqewQEhKIt99uLlF1RKZjaanArFmvIiLiTbRvrz+Y48WLqejXbx8++eQ00tOfSVBh1cVQqCJ++SUV/frtxXff/aa37LXXPHH8+Jscx4hqnBYtXHHo0FAsWtQVtra6h0sFAdi69Ra6dNmJtWuv4vnzQomqrFoYCmYuN7cAc+acQ0BACG7dytJZJpfL8MknHYq8ZI+oplAo5Jg8uQ1Onx6Jfp+tpyAAAArcSURBVP3q6S3PycnHwoUX0KXLTmzefAP5+ZoiHoX+wFAwU1qtgODgOHTrthMbN8bg5fNm3t72OHBgMGbPflXvuCpRTVS/vgO2bRuAHTsGoHFj/ftykpOfYsaMM+jWLRg7dtzi6KvF4LuJGfr552T4++/Hxx+fRGqqWm/5mDFNcfLkCHTpopKgOiLz1qdPPZw6NQKLFnWFUmmltzwxMQfTpp1G5847sH79NeTk5EtQpfliKJiR8+eT8eabYRg6NAzR0fpXTtSrp8Tu3YOwatXrcHS0LuIRiAgArKwUmDy5DS5cGIMPPmgNa2uF3joPHuRi/vzzaNt2K+bN+xkJCZztDWAoSK6wUIuwsHsIDAzBkCFhepeZAoCVlRxTp7bD6dMj0auXtwRVElVNbm42WLy4Gy5degvjx7eApaX+W15ubgG+++43dOq0AyNHHsTevbehVtfceaJ5d5NEkpNzsXv3bWzefANJScVPIDJ4cEPMn98Z9es7mLA6oupFpbJDUFAPfPRRO/z731ewa1cc8vJ0TzgLAnD6dBJOn06Cvb0lhg5thDffbIwuXVQ16rwdQ8GEHj9WY8eOW9i79w7OnHmod/L4r3r29MKMGb6cHY3IiOrWVWL58p6YPftVbN58Az/8cB2PH+vfx5CbW4CtW29h69ZbcHKyRt++9eDvXx9+fnVhb69/nqI6YShUosJCLX777THOnk3GiROJuHAhFVptybff9+zphU8/7ciTyESVyM3NBp9+2hEffdQW+/ffwQ8/XMfVq4+LXDc7Ow979tzGnj23YWkpR/v27ujWTYWuXVV49dU6sLe3NHH1lYuhYESZmc8RE/MYV68+xvnzKbhwIQW5uaUfm6xVS4ERI5pg4sRWaNGCcx4QmUqtWhZ4663meOut5rh5MxPBwbHYvft2sXdBFxRocelSKi5dSsW//30FFhZytGzpgjZtaqNVq9po06Y2WrRw1Ru0ryqpupVLpLBQi4cPc3H//hMkJDzB/ftPEBeXhZiYDCQnl22ExrZta2PMmGYYNqwxRzMlkpiPjwsWLuyKuXM74+TJBwgNvYfjxxNLnK+hsFCLq1cf63zLkMtl8Pa2R6NGjmjUyAmNGjmiXj0l6tSxg0plB1dX8/5bN4tQiI+Px+zZs5GdnQ0nJycEBQWhQYMGlbrPwkItsrLykJubj9zcAjx9WoCcnBc/5+a++Dk9/dl//6nx6NGLnzMynkGjKf8IjC1auGDAgAYIDGwEHx8XI/aIiIzBwkKOfv3qo1+/+igs1OKXX1Jx+HACjh1LwL17v5e6vVYrIDExB4mJOTh5MklvuZWVHJ6e9nBzs4G7uy2cnKzFf46O1nB2toZSaQVbWwvY2lrAxubFP1tbS9jYWKBWLQVkL09HZ0RmEQoLFizA2LFjMWTIEISEhGD+/PnYsmVLpe1v3747mDv35yJPMBmbq2stdOvmiW7dVBg50gcODvrXSxORebKwkKNrV0907eqJRYu6Ijk5Fz//nILz55Nx7lyKQSHxsvx8Le7ff3GUoTxkMsDaWgF3d1t8+GFbjB/fslyPUxzJQyEjIwM3btzApk2bAAABAQFYvHgxMjMz4eJi2CfpsgwTLQgCVq26Ajs7S9jZGfcEkaWlHA0bOqJpUye0aOGKDh3c0aiRo5jqrq72yMgo/vLTqsbQ593Z2REODuW7YsPZ2bFCw4Abum87O0vIZLrDHqhU7uWuW+rttVoHkzxvJW1v7OHbzWE4eG9vJUaNUmLUqKYAXpxHvHUrC7GxmYiNzcLNm5klXmJubOvX/wZ//wbw8rIv03YlPZcyQeLZKGJiYjBr1iwcPHhQbBs4cCCWLl2Kli2Nm4BERFSymnNHBhERlUryUFCpVEhLS4NG8+LuQo1Gg0ePHkGl4nX6RESmJnkouLq6wsfHB+Hh4QCA8PBw+Pj4GHw+gYiIjEfycwoAcPfuXcyePRtPnjyBg4MDgoKC0LBhQ6nLIiKqccwiFIiIyDxIfviIiIjMB0OBiIhEDAUiIhIxFIiISCT5MBdVnSGD+c2cOROxsbHi77GxsVizZg369OmDjIwMfPbZZ0hJSUFhYSE6d+6MuXPnwsJCmpfGkP6UVLNGo8GXX36JM2fOQCaT4f3338fIkSMl6QtQ8f6sWbMGhw4dglwuh6WlJaZPn44ePXpI0xlUvD9/uHfvHoYNG4axY8di1qxZJu7Fn4zRn0OHDmHdunUQBAEymQybNm1C7dq1q1xfzOa9QKAKGTdunHDgwAFBEAThwIEDwrhx40pc/+bNm0KnTp2EvLw8QRAE4csvvxT+9a9/CYIgCPn5+cKIESOEgwcPVm7RJTCkPyXVvH//fmHChAmCRqMRMjIyhB49eggPHjwwXQdeUtH+REVFCWq1WhCEF69dx44dhWfPnpmoen0V7Y8gCEJhYaHwzjvvCJ988om4nlQq2p9r164JAwYMEB49eiQIgiA8efJEeP78uYmq11XRvpjLewEPH1XAH4P5BQQEAHgxmN+NGzeQmZlZ7DZ79uzB4MGDYWX1YrAxmUyGp0+fQqvVIj8/HwUFBfDw8DBJ/S8ztD8l1Xzo0CGMHDkScrkcLi4u6Nu3L44cOWLyvgDG6U+PHj1gY2MDAGjWrBkEQUB2drZpO/JfxugPAGzYsAG9e/eu9OHpS2OM/vz444+YMGEC3NzcAABKpRLW1tam7QiM0xdzeS9gKFRASkoKPDw8oFC8GA5boVDA3d0dKSkpRa6fn5+PsLAwDB8+XGybMmUK4uPj0b17d/Ffx44dTVL/ywztT0k1p6SkwNPTU1xXpVIhNTXVdJ34C2P0568OHDiAevXqoU4daebNNkZ/bt26hbNnz+Ldd981dfl6jNGfu3fv4sGDB3j77bcxbNgwrF27FoIEt14Zoy/m8l7AUDChiIgIeHp6wsfHR2w7cuQImjVrhrNnzyIqKgqXL1+W7JO1oapizSUxpD+XLl3CypUrsXz5comqNFxx/SkoKMC8efPwxRdfiG9eVUFJr49Go0FsbCw2bdqEn376CVFRUQgJCZG44uKV1Bdz+btiKFRAWQfz27t3r863BADYunUrAgMDIZfLoVQq4efnh4sXL1Z67UUxtD8l1axSqZCcnCyum5KSItkna2P0BwCuXLmCGTNmYM2aNZIOv1LR/qSnpyMxMRHvv/8+/Pz8sHnzZuzatQvz5s2TojtGeX08PT3h7+8PKysr2Nvbo0+fPrh27VqV7Iu5vBcwFCqgLIP5paam4tdff8XgwYN12r29vREVFQXgxeGl8+fPo0mTJpVffBEM7U9JNfv7+2P37t3QarXIzMxEREQE+vfvb9qO/Jcx+nPt2jVMnz4dq1atknx+j4r2x9PTExcvXkRkZCQiIyPxP//zPxg1ahQWL15s8r4Axnl9AgICcPbsWQiCgIKCAly4cAHNmzc3bUdgnL6Yy3sBxz6qoOIG85s0aRKmTp2K1q1bAwDWrVuHuLg4rFixQmf7xMRELFiwAI8fP4ZGo0Hnzp3x+eefS3ZJqiH9KalmjUaDRYsW4dy5cwCASZMmYfTo0ZL0xRj9GT58OB4+fKhzwm/JkiVo1qxZlezPX61evRpqtVrSS1Ir2h+tVougoCBERUVBLpeje/fumDVrFuRy03/erWhfzOW9gKFAREQiHj4iIiIRQ4GIiEQMBSIiEjEUiIhIxFAgIiIRQ4GIiEQMBSIiEjEUiIhI9P874i6w3Hf+qAAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"viYsNMRRL4PI"},"source":["### Random Forest - Create a GridSearch to identify the best classify"]},{"cell_type":"code","metadata":{"id":"2dxWlKiqly2Z","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750516124,"user_tz":180,"elapsed":1542,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"72e1eef3-24ed-4920-f847-cb98766752eb"},"source":["\n","filename = 'best_model_rf.sav'\n","\n","if run_grid_search_rf == True:\n","  # Create the parameter grid based on the results of random search \n","  # parameters in https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html\n","  param_grid = {\n","      'max_depth': [1, 6, 12],\n","      'bootstrap': [True, False],\n","      'n_estimators': [10, 100, 200],\n","      'min_samples_leaf': [1, 10, 20, 40],\n","      'ccp_alpha': [0.0, 0.4],\n","      'criterion': ['gini', 'entropy'],\n","      'max_features': ['sqrt', 'log2']\n","  }\n","\n","\n","  # Create a based model\n","  model_rf = RandomForestClassifier()\n","  # Instantiate the grid search model\n","  #https://scikit-learn.org/stable/auto_examples/model_selection/plot_cv_indices.html#sphx-glr-auto-examples-model-selection-plot-cv-indices-py\n","  grid_search = GridSearchCV(estimator = model_rf, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","  \n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  \n","  grid_search.best_params_\n","\n","  model_rf = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_rf, open(filename, 'wb'))\n","  files.download(filename)\n","else: \n","  #load\n","  model_rf = pickle.load(open(filename, 'rb'))\n","\n","print('Parameters of best model:')\n","print(model_rf)\n","y_pred_rf = model_rf.predict(X_test)\n","\n","#Fitting 10 folds for each of 864 candidates, totalling 8640 fits"],"execution_count":40,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,\n","                       criterion='gini', max_depth=12, max_features='log2',\n","                       max_leaf_nodes=None, max_samples=None,\n","                       min_impurity_decrease=0.0, min_impurity_split=None,\n","                       min_samples_leaf=1, min_samples_split=2,\n","                       min_weight_fraction_leaf=0.0, n_estimators=100,\n","                       n_jobs=None, oob_score=False, random_state=None,\n","                       verbose=0, warm_start=False)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"FwINsXaWL4PM"},"source":["RF - Accuracy, precision and Recall"]},{"cell_type":"code","metadata":{"id":"p-FtQrE0L4PM","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750516125,"user_tz":180,"elapsed":1536,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"883d9e60-f8a0-48c0-c9dc-d488a63d42e2"},"source":["y_pred = y_pred_rf\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":41,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.759136</td>\n","      <td>0.773026</td>\n","      <td>0.755627</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.759136   0.773026  0.755627"]},"metadata":{"tags":[]},"execution_count":41}]},{"cell_type":"markdown","metadata":{"id":"M0GRxFj1L4PQ"},"source":["RF - Confusio matrix"]},{"cell_type":"code","metadata":{"id":"juEXd6PfL4PQ","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750517140,"user_tz":180,"elapsed":2544,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"84b4317f-ecac-4292-a395-42da486c24dd"},"source":["plot_confusion_matrix(model_rf, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":42,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAT8AAAEMCAYAAACySLGoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3deVxU5f4H8M+ZYRMRWYRpcOOK27yua+GaOymGY5RleCG1urkldi1vinQDl9Iwte51LbtqBt0Ml4wRf5pLmZZb1wUjURFTcYCUjGQRGOb3BznXiWUOdmaYmfN5+zqvmHOeec73YH17lnOeIxiNRiOIiGRG0dgBEBE1BiY/IpIlJj8ikiUmPyKSJSY/IpIlJj8ikiUmPyKSROEvxY0dQoMIjnKf37BnlyO34FZjhyGprPQF6BSR0NhhWMWZzxc0dghW4e4C3Kls7Cik5+4iTT1hz7+La/n1/3faSuWDfetnSnPCP0CiS7a+3IJbuKIvbOwwJOeM1wQADvF/1PvkbNcmSFjXtYJfcCXvZwsnlPKM989hkh8ROQBBAAQLo2lMfkTkdATBcnJj8iMip6NQVm+WytgBJj8iko6gENHttY+bTJj8iEhCIrq9kk6x3D8mPyKSDic8iEiWOOFBRLLEMT8ikiXO9hKRLHHMj4hkSRAABcf8iEhuOOZHRLLE2V4ikiWFQsSEB1t+RORs2O0lIllit5eIZIktPyKSJy5sQERyxJuciUiWrPB4W05ODuLi4nDr1i34+PggKSkJwcHBZmVmz56NrKws0+esrCysWrUKYWFhddbL5EdE0rHCmF9iYiKio6MRGRmJHTt2ICEhAZs2bTIrs2TJEtPP586dw8SJEzFw4MB667WPkUcicg53Z3stbSLdvHkTmZmZ0Gq1AACtVovMzEwUFtb91sMtW7Zg9OjRcHNzq7dutvyISDoNGPPT6/UwGAxmh7y9veHt7W36rNfroVKpoFRWd5WVSiUCAwOh1+vh5+dXo+ry8nKkpaVh48aNFkNl8iMi6TTgPr+YmBjk5uaaHYqNjcWMGTPu+/R79+5FUFAQNBqNxbJMfkQkIRFjfr+NtqWkpNTa8ruXWq1Gfn4+DAYDlEolDAYDCgoKoFara61569atePLJJ0VFyuRHRJIRFAoIFp7dvXu8rgR2L39/f2g0Guh0OkRGRkKn00Gj0dTa5c3Ly8N3332H5cuXi4qVEx5EJBlBEERtDTFv3jwkJycjPDwcycnJmD9/PgBg0qRJyMjIMJXbvn07hg4diubNm4uqly0/IpKOAMsPcDTwHueQkBCkpqbW2L9u3Tqzz9OmTWtQvUx+RCQZMS27hrb8rIXJj4gkUz3Zayn52SgYC5j8iEgyCkEBhYUJDwVXdSEip2OFMT9rYfIjIslwzI+I5EnMrSxMfkTkbNjyIyJZYvIjIlkSFAIEhYXkZ+G4rTD5EZFkBIi4z882oVjE5EdEkmG3l4jkiff5EZEcseVHRLLE5EdEsiQoLD/ba2mxU1th8iMi6XDMj4jkSICIbq+dZD8mPyKSjCON+dlH59uJ+Hh74qMlk3Dt4DKc+XwBngoPrbVc6j+noawSuPrVMlz9ahnyv3kXh/8Tb1ZmyrghOPXZPFw7uAxHPv0HQtoE2uISZOXnX4rxzKvvo+XAV9B19OtI/b/jtZb710d70S/qTQQ8PAvdIxPxr4/21lru8HcX4NsrFm+sSbNm2Hbr7mKm9W+NHWU1tvwktnT20yivrESn8Lno2rEVNr87DWcvXMO5S3lm5cb+bQ1KT66E7+BZAIC0tX/DwRNZpuPjI/th/GP9EPXyWmTl5CG4ZQvc+rXEptciB39f8incXFyQtXsxMs5fQ9TMNejSoRU0IeZvFjMajVg7fwIe6hyEHy7fwJgZK9FS5YMnR/zvf24VlQbELduC0C7BNr4K++FIj7fZrOWXk5ODqKgohIeHIyoqCpcvX7bVqW3G08MNo4f1wKK1O1FcWo4jpy9h18EMREX0rvd7rdV+6NcjBJ/sPAag+v+ccyZFIP6drcjKqU6al3Nv4FYRk5+UikvvIG3/KcRPHQUvT3f06xGCRwd1xeb0YzXK/m3CcHTv3BouLkp0CFYhYnA3HD19yazMyuR9GNpXgw5tVba6BLtjjbe3WYvNkl9iYiKio6Oxe/duREdHIyEhwVantpmQNoGoNFQh+0qBad/ZC7no3K7+95OOG9Ub357KxlV9IQCgZaAPWqp8oQkJwlndQpz6bB7iJkfYzb80ziL7SgFclAq0vydZdenQEucu6ev9ntFoxLcns83+Xq/oC5GS9i1mv/Co1eJ1BEx+v3Pz5k1kZmZCq9UCALRaLTIzM1FYWGiL09uMl6c7fi0uM9tXdLsUXp4e9X5vXEQffKw7YvocpPIBAAzr0xn9xy3C6Gn/wpMjQjE+sp/0QcvY7ZI7aNbU/O/G26sJbpeU1fGNam+9n44qoxExo/ua9sUtTUX8FC28PN2tEqvDEJP47CT52WTMT6/XQ6VSQalUAgCUSiUCAwOh1+trffN6bbLSF1gzRElUGYFyA1B6cqVpX2VV9f57992r+L8rUW4A/r1gPNYvHG9Wj3ZwF+R//bapnhX/iMZ7idHWvxCZ8Gvmjl9LyuBxz38FpaVlaO7lYbbvXms++Qqb049h7/qZaO7pCgDY+VUGSkrvIDriIQCAUgG4KFBnHU7PPnKbRQ7z19MpIgFX9PbdUvT0cEPO/iV4aMybuHT1JwDAmnnjkXfjF8xf+XmN8qUnV2Ld1sNwd3XBtHkfmfY3cXdFzv4lGBW7Et+czAYAvBg9DP16hGD87HU16rFHPx+vPdnbk9YtA1FZWYXvLxWYZtJPZeWiQ7AaZZU1yyd//i2WbvgCO9+biRb+vqYye49k4b+ZV9A2bC4AoKi4DEqFgDPnr+PjZVNsdTn3TQDgLlEm4K0uv6NWq5Gfnw+DwQAAMBgMKCgogFpd/1iYoykpK4fuwGnETxkFTw839OnWDhGDu9U6gA4ARiPwxCMP4mPdUbP9pXcqsP2L/+Kl8cPh5emOoEAfTHyiP3YfOmuLy5CNpk3coR3aHYve24ni0js4cjob6V+dqXWC6tNdx7Fw1efYuSYWwa1amB2Ln6rF8S0JOJgyFwdT5uLRgV0x4fGHsSrhGVtdit1QKARRmz2wSfLz9/eHRqOBTqcDAOh0Omg0GtFdXkcyK2kzPNxdcX7PYnzw5rOY9dZmnLuUh349QnD1q2VmZauMwC+/luLrE+dr1DP77VQUl95BZvqb2LN+FrbsPoHkz7+11WXIxrI5USi7U4GOI+bihdc2YllcFDQhanxz8iJaDXrFVO7NtToU/lKMAc8sQatBr6DVoFfw8uL/AACaNfWAqoW3afNwd4VnEzf4Nm/aWJfVaBxpwkMwGo1GW5woOzsbcXFxKCoqgre3N5KSktCuXTvR33eEbm9DlZ5ciSY9Yxs7DKtwhG7v/fBwQa1dYkcmZbd36OKvkPtzab1lWvo2wYG5g6U54R9gszG/kJAQpKam2up0RNQI7j7hYamMPXCYCQ8isn9i7mRh8iMipyMIlic07GXMj8mPiCQjZjbXXmZ7mfyISDLs9hKRLFnjJuecnBzExcXh1q1b8PHxQVJSEoKDg2uUS09Px5o1a2A0GiEIAjZs2IAWLVrUrPA3TH5EJBlrJL+7i6JERkZix44dSEhIwKZNm8zKZGRkYOXKlfjwww8REBCAX3/9FW5ubvXWy8VMiUgyd7u9ljag+pn/a9eumW1FRUVm9YldFGXjxo14/vnnERAQAABo1qwZ3N3rX2SCLT8ikkxDZntjYmKQm5trdiw2NhYzZswwfRa7KEp2djZatWqFmJgYlJSUYPjw4Zg2bVq9rUwmPyKSTEO6vSkpKabn/e/y9va+r/MaDAZkZWVhw4YNKC8vxwsvvICgoCA8/vjjdX6HyY+IJNOQ2V4xC5vcuyiKUqmsc1GUoKAgjBw5Em5ubnBzc0NYWBjOnDlTb/LjmB8RSUbqhQ3ELoqi1Wpx6NAhGI1GVFRU4MiRI+jcuXO9dTP5EZFkGjLhIda8efOQnJyM8PBwJCcnY/78+QCASZMmISMjAwAwatQo+Pv7IyIiAo8//jjat2+Pp556qt562e0lIslYY2GDuhZFWbfufwv7KhQKzJ07F3PnzhVdL5MfEUmGz/YSkSzx8TYikiVHeocHkx8RSYYtPyKSJbb8iEiWmPyISJa4mCkRyZadNOwsqjP5vfrqq6Kap0uWLJE0ICJyXE7R7W3btq0t4yAiJ+AUs72xsc75Mm0ish6FIEBhIbtZOm4rosf8Dh8+jJ07d6KwsBBr165FRkYGbt++jX79+lkzPiJyIAqF5QkNhZ0spyIqjI8++gjz5s1DcHAwjh8/DgDw8PDAP//5T6sGR0SORRAAhYXNThp+4pLfhx9+iA0bNmDy5MlQ/Ja227Vrh5ycHKsGR0SORer1/KxJVLe3uLjYtHLq3cArKyvh6upqvciIyOEIEDHhYZNILBPV8uvVqxfef/99s32bNm1Cnz59rBIUETkmQeQfeyCq5fePf/wDU6dORWpqKoqLixEeHo6mTZvivffes3Z8RORA7o7rWSpjD0Qlv8DAQGzduhUZGRnIzc2FWq1Gt27dTON/RESAkz7eVlVVhYqKCgDVr4kzGo1WC4qIHJMg4j4/h5rwOHfuHKZPn47y8nKoVCrk5eXB3d0dq1atsviGJCKSD6d4wuNe8fHxiImJwXPPPQdBEGA0GrFx40bEx8dj27Zt1o6RiByEIz3bK2rQ7vLly5g4caIpaEEQMGHCBFy+fNmasRGRg7HGqyutRVTyGzx4MPbv32+278CBAxgyZIg1YiIiB6WEAKVgYbP3W13uXdLKYDDg5ZdfRpcuXfDAAw8gLy8PZ8+eRVhYmM0CJSIHIOYJDjtp+ole0qpjx46mn9u3b48BAwZYLyoickhOcZ8fl7QiooaqHtOzNOFho2AsEH2fX3l5OXJycvDzzz+b3ePHJa2I6C6nu9XlxIkTmDlzJsrLy3H79m14eXmhuLgYDzzwAPbt22ftGInIQTjSrS6ikt/ixYvxwgsv4Nlnn0WvXr1w7NgxrFy5Ek2aNLF2fETkQBQKAUoHebxN9H1+EyZMMNs3efJkbNy40RoxEZGDEkRu9kBU8mvWrBlu374NAAgICMDFixdRVFSEkpISqwZHRI5FAcH0Ho86NztJf6K6vcOHD8dXX32F0aNH48knn8SECRPg4uKC8PBwa8dHRA7E6SY8XnvtNdPPf/3rX9G9e3cUFxdj4MCBVguMiByPNSY8cnJyEBcXh1u3bsHHxwdJSUkIDg42K7NixQp8/PHHCAwMBAA8+OCDSExMrLde0be63Cs0NPR+vkZETs4aLb/ExERER0cjMjISO3bsQEJCAjZt2lSj3OOPP445c+aIrrfO5BcdHS0qQ6ekpIg+GRE5N6lne2/evInMzExs2LABAKDVarFw4UIUFhbCz8/vD8VaZ/IbO3bsH6pYaic/mw9nXD71xtEVjR2CVfj2ndnYIVhF6Yl3ne7a2qj9kJWWIEldDen26vV6GAwGs2Pe3t7w9vY2fdbr9VCpVFAqlQAApVKJwMBA6PX6Gslv586dOHToEAICAjBjxgz07Nmz3jjqTH5PPPFEvV8kIvo9BSzfQnL3eExMDHJzc82OxcbGYsaMGQ0+77hx4zB16lS4urri8OHDePHFF5Geng5fX986v3NfY35ERLVpSMsvJSWl1pbfvdRqNfLz82EwGKBUKmEwGFBQUGB6le5dAQEBpp8ffvhhqNVqXLhwAb17964zDiY/IpKMAiJWdfntn79PYLXx9/eHRqOBTqdDZGQkdDodNBpNjS5vfn4+VCoVAOCHH35Abm4u/vSnP9VbN5MfEUlGoYCICY+G1Tlv3jzExcVh9erV8Pb2RlJSEgBg0qRJeOmll9C1a1csX74c33//PRQKBVxdXbFkyRKz1mBtmPyISDLWWM8vJCQEqampNfavW7fO9PPdhNgQonJweXk53nnnHYSFheGhhx4CABw6dAjJyckNPiEROS+ne4fHokWLcP78eSxdutQ0WNmhQwf85z//sWpwRORYLD7XK+K9vrYiqtu7d+9e7NmzB56enlD81mFXqVTIz8+3anBE5FgEWG5R2UfqE5n8XF1da0xJFxYWwsfHxypBEZFjcqSFDUR1e0eOHIk5c+bg6tWrAICCggIsWLAAo0aNsmpwRORYlEL14231bnaS/UQlv5dffhmtWrXCY489hqKiIoSHhyMwMBDTp0+3dnxE5EDuzvZa2uyBqG6vm5sb4uPjER8fj8LCQvj6+trNOvxEZD8EERMa9pI7RCW/u93du4qLi00/t27dWtqIiMhhOdKYn+iVnAVBMHtl5d3s/cMPP1gnMiJyOE7x0vJ7nTt3zuzzTz/9hJUrV3JRUyIyI/z2x1IZe9DAp+yqBQQE4LXXXsPy5culjoeIHJhSAbhY2JT3lXWkd9/P9l66dAmlpaVSxkJEDs7pXlr++yXtS0tLcfHiRd7qQkRmGrKkVWMTlfx+v6R9kyZN0Llz5xpvUCIieXOq2V6DwYAjR45g4cKFcHNzs0VMROSgxCxc4DALGyiVShw+fNhu+ulEZL8UIiY0GrqYqbWICmPixIlYsWIFKioqrB0PETkwBQRRmz2ot+Wn0+mg1WqRnJyMGzduYMOGDfDz8zNrBX755ZfWjpGIHITTjPklJCRAq9Xi7bfftlU8ROTAnOYJj7uPs9X3+jciorsEwfKEhkO0/KqqqnDkyBGzZ3p/r1+/fpIHRUSOSYCIbq9NIrGs3uRXXl6O1157rc7kJwgC9u3bZ5XAiMjx3F2w1FIZe1Bv8mvSpAmTGxGJpoDlW0js5E4XvreXiCQk4tleexn0EzXhQUQkhgDLY3r2kfosJL+TJ0/aKg4icgJO9XgbEZFYTtPyIyJqCIVCgMLCbK6l47bC5EdEkhFgeTbXPlIfkx8RScjpVnImIhKDY35EJEsCRLT87CT92cvN1kTkBJSCIGpriJycHERFRSE8PBxRUVG4fPlynWUvXbqE7t27IykpyWK9TH5EJBlB5NYQiYmJiI6Oxu7duxEdHY2EhIRayxkMBiQmJuKRRx4RVS+THxFJR/jfgqZ1bQ3Jfjdv3kRmZia0Wi0AQKvVIjMzE4WFhTXKvv/++xgyZIjoF6sx+RGRZKoXNrC0jH01vV6Pa9eumW1FRUVm9en1eqhUKiiVSgDV7xQKDAyEXq83K3fu3DkcOnQIzz77rOhYOeFBRJJpyDL2MTExyM3NNTsWGxuLGTNmNOicFRUVeP3117F48WJTkhSDyY+IJCP89sdSGQBISUmBwWAwO+bt7W32Wa1WIz8/HwaDAUqlEgaDAQUFBVCr1aYyP/30E65cuYLJkycDAIqKimA0GnH79m0sXLiwzjiY/IhIMmJmc+8evzeB1cXf3x8ajQY6nQ6RkZHQ6XTQaDTw8/MzlQkKCsLRo0dNn1esWIGSkhLMmTOn3ro55kdE0pF4wgMA5s2bh+TkZISHhyM5ORnz588HAEyaNAkZGRn3HSpbfkQkGWu8ujIkJASpqak19q9bt67W8mLHDJn8iEgyDRnza2xMfkQkGad5by8RUUMoIGIlZztp+XHCQ2I//1KMCbPXoc3gWegRmYAtu0/UWm7FR3vx0FNvou3Qv+PBxxOx4qO9tZY7/N8LaNFnBhat1VkzbNny8fbER289j2sHknBmewKeGvFgreVS35mCq/uTUFYJXN2fhPyvl+Jw8myzMlOeHoRT217HtQNJOPLJXIS0DrDFJdgVQeQfe2CTll9SUhJ2796N3NxcpKWloWPHjrY4baOY/fancHVVInPXIpw9fw1/eWUtunRoic7tzKf1jQA+WDgB7dqqkZN7A2NfWoWWKl+MGfGQqUxFpQGvLd+Kh/4cbNuLkJGlf38K5ZUGdIp4HV07tsTmZZNx9sJ1nMvJMys39uX3AAClJ96F77A5SFsdi4MnLpiOj3+sL8Y/1hdRr7yPrMv5CG7pj1u/ltr0WuyBIKLbayfL+dmm5RcWFoaUlBS0bNnSFqdrNMWld6A7cBpzp2jh5emOvj1CMHJgV3y661iNsi+NfwQ9Na3h4qJEh7YqPDqoG46duWRWZnXKPgzp0xkdggNtdQmy4unhhtFDu2HRe+koLi3HkdM52PX1WUQ9Glrv91qr/dCvezt8sus4gOrFOef8NRzx725H1uV8AMDl3Ju4VVRi9WuwN47U8rNJ8gsNDRV1Q6Ojy75SABelAu3b/C9Z/blDS5y7lFfPt6pfEXrkVDY63dM6vKovREraEfz9r49aLV65C2kTgEpDFbKv/mTad/bCdXRu90C93xv3aC98e/oSruqrH65vGdgcLVW+0LRT4+yORJza9jriXhhpNysW25Kle/zE3ApjK5zwkFBxyR00a+phts/bywO3S8rq/V7SunRUVVUhWtvHtG/usi2YO2UUvDzdrRIrAV5N3PFrsfnfTVFxKbw8Per4RrVxj4Zi6cYvTJ+DAn0AAMP6dEL/mCVo3qwJtv1zKq7/dAubdhyRPnA7xpWcrcDTzV5+ZXVr0dwDv5aUoek9sd4puwMfLw+zfffatO0gUncdx971M+Hn5QYA2PlVBkrL7uCZUdXdLxeFAFcl6qzDHpWeeLexQ7CoygiUG8xjrayq3l9X/FVGoF3rAPx7XjTWz482q0c76M/I/3KxqZ4V8ePw3uvjrH8hdqQhj7c1NodJfiXlRhgbOwgLgtQBqKyswpmL+Qj5ret78tw1tA9+AMXlNaPfkn4Eb6//Amnv/Q2+vj6mMl98m4Xvvr+CtmFzAQBFxWVQKgSczrqO5KWTbXdBf0CL/i83dggWeXq4IeeLRXho7Fu4dPUGAGBNQgzybvyC+atrn10vOvouPkk/jmkLUkz7mri7IueLxRj10mp8c6p63PbFvwxBv+7tMD5uvfUv5A9qo/ZDVlrtC4Q2mAM1/Xiri4SaNnHHqCHd8db7O1FcegdHT1/CroMZePrR3jXKpv7fcSSu/BxbV0xHcMsWZsfipozC0S2v40ByHA4kxyF8YBc8E9kfK16PsdWlyEJJWTl0X55B/KQIeHq4oU+3PyFiUBds3lX77Uke7q4wGIGPd5pPYJXeqcD2vSfx0jNh8PJ0R1BAc0yM7Ifdh7+3xWXYHUeY7ABslPzeeOMNDBo0CHl5eXjuuecwatQoW5y2Ubw9+2mU3amAZmQ8Jr++EW/PiULndmp8e/Ii2g6ZZSq3eK0ON38pxvDn3kbbIbPQdsgszHrrEwBAs6YeUPl7m7Ym7q5o2sQdvs2bNtZlOa1Zb2+Bh7srzu9aiA8WTMCsJak4l5OHft3b4ep+8/dAjBrUFQDw9XcXatQze+kWFJfeQWbafOz5YCa27PkvktOO1ijn7BxpwkMwGo323psE4Bjd3oZq6ibU2h12Bo7Q7b0fpSfeRZPQmY0dhqSk7PaevlKE8sr6/512cxHQvY13vWVswWHG/IjIATjQmB+THxFJRiEIIhY2sI/sx+RHRJJxoIYfkx8RScxespsFTH5EJBkxN7PYy+0uTH5EJBlrLGNvLUx+RCQdMffxMfkRkbNht5eIZIndXiKSJd7qQkTy5EDZj8mPiCTDMT8ikiW+t5eI5IndXiKSI3Z7iUieeJMzEcmRA/V6mfyISGL2kt0sYPIjIslwMVMikiV2e4lInqyQ/XJychAXF4dbt27Bx8cHSUlJCA4ONiuzdetWbNy4EQqFAlVVVRg7diwmTJhQb71MfkQkGWvc6pKYmIjo6GhERkZix44dSEhIwKZNm8zKhIeHY8yYMRAEAbdv38bo0aPRu3dvdO7cuc56+dJyIpJMQ97bq9frce3aNbOtqKjIrL6bN28iMzMTWq0WAKDVapGZmYnCwkKzcl5eXhB+q7isrAwVFRWmz3Vhy4+IJNOQJa1iYmKQm5trdiw2NhYzZswwfdbr9VCpVFAqlQAApVKJwMBA6PV6+Pn5mX133759WL58Oa5cuYJZs2ahU6dO9cbB5EdEkhLbrU1JSYHBYDDb5+19/y8zDwsLQ1hYGK5fv47p06dj0KBBaNeuXZ3lmfyISDINafmp1WqL9anVauTn58NgMECpVMJgMKCgoKDe7wYFBaFr16748ssv601+HPMjIskIIjex/P39odFooNPpAAA6nQ4ajaZGlzc7O9v0c2FhIY4ePYqOHTvWWzdbfkQkGWssYz9v3jzExcVh9erV8Pb2RlJSEgBg0qRJeOmll9C1a1ds3rwZhw8fhouLC4xGI5555hkMGDCg/jiMRqOxYaE0jpJyIxwi0AZo6iaguNzZrqpai/4vN3YIVlF64l00CZ3Z2GFIqo3aD1lpCZLUpf+lHIaq+ssoFYC6uZsk5/sj2PIjIskoBMDIxUyJSG4EiOj22iQSy5j8iEgy4p7wsA9MfkQkHTGZzU6yH5MfEUnKTnKbRUx+RCQZQRCxqIudZEcmPyKSjCCIGPNj8iMiZ8PFTIlIltjtJSJZ4q0uRCRLbPkRkSwx+RGRTDX0DR2Nh8mPiCQjplXHlh8ROR0HerqNyY+IJGYv2c0CJj8ikoyYET97yY1MfkQkGYUAiyuuM/kRkfOxl8wmgsMkPwf6nTaIs15XG7Wf5UIOytmurWVgc8nqUggCLL0VyF5mex3mBUZERFLie3uJSJaY/IhIlpj8iEiWmPyISJaY/IhIlpj8iEiWmPyISJaY/IhIlpj8iEiWmPwaQU5ODqKiohAeHo6oqChcvny5sUOieiQlJWHYsGHo1KkTzp8/39jhkESY/BpBYmIioqOjsXv3bkRHRyMhIaGxQ6J6hIWFISUlBS1btmzsUEhCTH42dvPmTWRmZkKr1QIAtFotMjMzUVhY2MiRUV1CQ0OhVqsbOwySGJOfjen1eqhUKiiVSgCAUqlEYGAg9Hp9I0dGJC9MfkQkS0x+NqZWq5Gfnw+DwQAAMBgMKCgoYLeKyMaY/GzM398fGo0GOp0OAKDT6aDRaODn51wLZBLZOy5m2giys7MRFxeHoqIieHt7IykpCe3atWvssKgOb7zxBvbs2YMbN27A19cXPj4+2LlzZ2OHRX8Qk/oE+yQAAAWZSURBVB8RyRK7vUQkS0x+RCRLTH5EJEtMfkQkS0x+RCRLTH6EuLg4vPPOOwCAEydOIDw83Cbn7dSpE3788cdaj40fPx6pqami6hk2bBi++eab+4rhj3yXHBuTn4MYNmwYunXrhp49e6J///6Ii4tDcXGx5OcJDQ3F7t27LZbbtm0b/vKXv0h+fiJbYfJzIGvXrsXJkyexfft2nD17FmvWrKlRprKyshEiI3I8TH4OSKVSYeDAgbhw4QKA6u5jSkoKRowYgREjRgAADhw4gMjISISGhmLcuHE4d+6c6fuZmZl44okn0LNnT8ycORN37twxHTt69CgGDRpk+qzX6xEbG4u+ffuiT58+WLBgAbKzs5GYmIhTp06hZ8+eCA0NBQCUl5cjKSkJQ4YMQf/+/ZGQkICysjJTXR988AEGDBiAAQMGYMuWLaKv98qVK5gwYQL69OmDPn36YNasWSgqKjIrk5GRgYiICPTq1Qtz5841u6b6fhckX0x+Dkiv1+PgwYPQaDSmfXv37sWnn36K9PR0ZGZmIj4+HgsWLMDRo0cRFRWFF198EeXl5SgvL8f06dMRGRmJY8eOYeTIkdizZ0+t5zEYDJgyZQqCgoKwf/9+HDx4EBEREQgJCcH8+fPRo0cPnDx5EidOnAAALF26FDk5Ofjss8+wZ88eFBQUYNWqVQCAgwcPYv369Vi/fj327NmDb7/9VvT1Go1GTJkyBV9//TV27dqFvLw8rFixwqxMWloa/v3vf+OLL75ATk4OVq9eDQD1/i5I3pj8HMj06dMRGhqK6Oho9OrVC1OnTjUdmzx5Mnx8fODh4YHNmzcjKioK3bt3h1KpxBNPPAFXV1ecOnUKp0+fRkVFBSZOnAhXV1eMHDkSXbt2rfV8Z86cQUFBAWbPng1PT0+4u7ubWnm/ZzQa8emnnyI+Ph4+Pj7w8vLClClTTM/A7tq1C2PGjEHHjh3h6emJ2NhY0dfdtm1bPPzww3Bzc4Ofnx+ee+45HD9+3KxMTEwM1Go1fHx8MG3aNNN56/tdkLy5NHYAJN6qVavQv3//Wo/duyTW9evX8dlnnyE5Odm0r6KiAgUFBRAEASqVCoIgmI4FBQXVWqder0dQUBBcXCz/a1JYWIjS0lKMGTPGtM9oNKKqqgoAUFBQgC5dupiONWRJ+Bs3buDNN9/EiRMnUFxcDKPRCG9vb7My915/UFAQCgoKANT/uyB5Y/JzEvcmM7VajalTp2LatGk1yh07dgz5+fkwGo2m71y/fh2tW7euUVatVkOv16OysrJGArz3fADg6+sLDw8P7Ny5EyqVqkZdv1+t+vr166Kvbfny5RAEAWlpafDx8cHevXuxYMECszK/rzswMNB0DXX9Lkje2O11QmPHjsUnn3yC06dPw2g0oqSkBF9++SVu376NHj16wMXFBZs2bUJFRQX27NmDjIyMWuvp1q0bAgICsGzZMpSUlODOnTv47rvvAFSvS5ifn28aO1MoFBg7diwWLVqEmzdvAgDy8/Px9ddfAwBGjhyJ7du34+LFiygtLcXKlStFX09xcTE8PT3RrFkz5Ofn44MPPqhR5uOPP0ZeXh5u3bqFtWvXIiIiwuLvguSNyc8Jde3aFQsXLsSCBQvQq1cvjBgxAtu2bQMAuLm5YcWKFdi+fTt69+6N9PR0DB8+vNZ6lEol1q5dix9//BFDhw7FoEGDsGvXLgBA37590b59ewwYMAB9+vQBALz66qto27Ytnn76aTz44IN49tlnkZOTAwAYPHgwJk6ciIkTJ2L48OHo27ev6OuJjY1FZmYmQkNDMXnyZNOM9r20Wi2ef/55PPLII2jTpo2ppVff74Lkjev5EZEsseVHRLLE5EdEssTkR0SyxORHRLLE5EdEssTkR0SyxORHRLLE5EdEssTkR0Sy9P+U+AMxTlLHuAAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"ZS_rZVSnL4PT"},"source":["RF - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"NsBmLK2NL4PU","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750518504,"user_tz":180,"elapsed":3901,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"764e26e1-3fed-4cec-a10b-332d311223e8"},"source":["\n","hit_rates = cross_val_score(model_rf, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_rf = hit_rates"],"execution_count":43,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"4Oxm18yNL4PY"},"source":["### XGBoot - Create a GridSearch to identify the best classify"]},{"cell_type":"code","metadata":{"id":"u7R5qLanyghr","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750519193,"user_tz":180,"elapsed":4582,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"0dc53ee6-9845-4a60-922f-635e6e1c883c"},"source":["filename = 'best_model_xgb.sav'\n","\n","if run_grid_search_xgb == True:\n","  # Create the parameter grid\n","  # parameters in https://xgboost.readthedocs.io/en/latest/parameter.html\n","\n","  param_grid = {\n","          'max_depth': [1, 6, 12],\n","          'n_estimators': [10, 100, 200],\n","\t        'min_samples_leaf': [1, 10, 20, 40],\n","          'booster': ['gbtree', 'gblinear', 'dart'],\n","          'sampling_method': ['uniform', 'gradient_based'],\n","          'tree_method': ['exact','approx','hist']\n","          }\n","  # Create a based model\n","  model_xgb = XGBClassifier()\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_xgb, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","\n","  model_xgb = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_xgb, open(filename, 'wb'))\n","  files.download(filename)\n","else: \n","  model_xgb = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_xgb)\n","y_pred_xgb = model_xgb.predict(X_test)\n","\n"],"execution_count":44,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n","              colsample_bynode=1, colsample_bytree=1, gamma=0,\n","              learning_rate=0.1, max_delta_step=0, max_depth=1,\n","              min_child_weight=1, min_samples_leaf=1, missing=nan,\n","              n_estimators=200, n_jobs=1, nthread=None,\n","              objective='binary:logistic', random_state=0, reg_alpha=0,\n","              reg_lambda=1, sampling_method='uniform', scale_pos_weight=1,\n","              seed=None, silent=None, subsample=1, tree_method='approx',\n","              verbosity=1)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"nrlw5SuXL4Pc"},"source":["XGB - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"JDXiFy21L4Pd","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750519195,"user_tz":180,"elapsed":4577,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"8352bb1d-5f8c-4770-ad49-f3427947077b"},"source":["y_pred = y_pred_xgb\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys\n","\n"],"execution_count":45,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.752492</td>\n","      <td>0.76129</td>\n","      <td>0.758842</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.752492    0.76129  0.758842"]},"metadata":{"tags":[]},"execution_count":45}]},{"cell_type":"markdown","metadata":{"id":"MqqSaN_rL4Pg"},"source":["XGB - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"bXtyjKl2L4Ph","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750519196,"user_tz":180,"elapsed":4570,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"a10d3670-5e91-496a-bd09-1167cb7ad4cd"},"source":["plot_confusion_matrix(model_xgb, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":46,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"lHDRZqsxL4Pk"},"source":["XGB - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"7UeyBHTtL4Pl","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750521876,"user_tz":180,"elapsed":7244,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"f865551b-d76b-45ea-c79a-5e4f81eb1287"},"source":["#del dataframe_analisys\n","hit_rates = cross_val_score(model_xgb, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_xgb = hit_rates"],"execution_count":47,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"ECNT_F17L4Po"},"source":["### Gradiente Boosting"]},{"cell_type":"code","metadata":{"id":"AkLYyZcg1nzC","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750521877,"user_tz":180,"elapsed":7238,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"3bc75505-9346-4d66-9292-ccef871f0cdd"},"source":["filename = 'best_model_gb.sav'\n","\n","if run_grid_search_gb == True:\n","  # Create the parameter grid\n","  # parameters in https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html\n","  param_grid = {\n","      'max_depth': [1, 6, 12],\n","      'n_estimators': [10, 100, 200],\n","      'min_samples_leaf': [1, 10, 20, 40],\n","      'learning_rate': [0.1, 0.5],\n","\n","      'loss': ['deviance', 'exponential'],\n","      'criterion': ['friedman_mse', 'mse', 'mae'],\n","      'max_features': [ 'sqrt', 'log2']\n","      }\n","\n","  # Create a based model\n","  model_gb = GradientBoostingClassifier()\n","\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_gb, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_gb = grid_search.best_estimator_\n","\n","  #save\n","  pickle.dump(model_gb, open(filename, 'wb'))\n","  files.download(filename)\n","else:\n","  model_gb = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_gb)\n","y_pred_gb = model_gb.predict(X_test)\n","\n","#Fitting 10 folds for each of 972 candidates, totalling 9720 fits\n"],"execution_count":48,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","GradientBoostingClassifier(ccp_alpha=0.0, criterion='mae', init=None,\n","                           learning_rate=0.1, loss='exponential', max_depth=12,\n","                           max_features='sqrt', max_leaf_nodes=None,\n","                           min_impurity_decrease=0.0, min_impurity_split=None,\n","                           min_samples_leaf=40, min_samples_split=2,\n","                           min_weight_fraction_leaf=0.0, n_estimators=100,\n","                           n_iter_no_change=None, presort='deprecated',\n","                           random_state=None, subsample=1.0, tol=0.0001,\n","                           validation_fraction=0.1, verbose=0,\n","                           warm_start=False)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"0tVsMlRtL4Pr"},"source":["GB - Accuracy, precision and recall."]},{"cell_type":"code","metadata":{"id":"mEyjviRIL4Ps","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750521877,"user_tz":180,"elapsed":7232,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"1b464441-0600-4fc5-d992-ab33e4b025bc"},"source":["y_pred = y_pred_gb\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":49,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.72093</td>\n","      <td>0.742373</td>\n","      <td>0.70418</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision   Recall\n","0   0.72093   0.742373  0.70418"]},"metadata":{"tags":[]},"execution_count":49}]},{"cell_type":"markdown","metadata":{"id":"-ppj0YcBL4Pu"},"source":["GB - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"SoADc31EL4Pv","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750522555,"user_tz":180,"elapsed":7904,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"8b2ebeb9-dbfc-45cf-95c9-dc6fba483d7b"},"source":["plot_confusion_matrix(model_gb, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":50,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"TdSspv0oL4Px"},"source":["GB - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"qy8FAjG0L4Py","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750541635,"user_tz":180,"elapsed":26979,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"802f506a-9a5f-4be3-e412-2f6c699c4568"},"source":["\n","\n","hit_rates = cross_val_score(model_gb, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_gb = hit_rates"],"execution_count":51,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"wwBEPtH6I26O"},"source":["### Logistic Regression - Create a GridSearch to identify the best classify "]},{"cell_type":"code","metadata":{"id":"awai_E89IicE","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750541636,"user_tz":180,"elapsed":26973,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"39b36261-350a-4f59-c605-8a26774f37fc"},"source":["filename = 'best_model_lr.sav'\n","\n","if run_grid_search_lr == True:\n","  # Create the parameter grid based on the results of random search \n","\n","  param_grid = {\n","      'solver':['newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga'],\n","      'penalty': ['l1', 'l2'],\n","      'C':[0.001,0.008,0.05,0.09,0.1],\n","      'max_iter':[50, 200, 400, 500,600]}\n","\n","\n","  # Create a based model\n","  model_lr = LogisticRegression()\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_lr, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), \n","                            n_jobs = 3, \n","                            verbose = 2,\n","                            scoring = 'roc_auc')\n","\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_lr = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_lr, open(filename, 'wb'))\n","  files.download(filename)\n","else: \n","  #load\n","  model_lr = pickle.load(open(filename, 'rb'))\n","\n","print('Parameters of best model:')\n","print(model_lr)\n","y_pred_lr = model_lr.predict(X_test)\n","#Fitting 10 folds for each of 112 candidates, totalling 1120 fits"],"execution_count":52,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","LogisticRegression(C=0.1, class_weight=None, dual=False, fit_intercept=True,\n","                   intercept_scaling=1, l1_ratio=None, max_iter=50,\n","                   multi_class='auto', n_jobs=None, penalty='l2',\n","                   random_state=None, solver='sag', tol=0.0001, verbose=0,\n","                   warm_start=False)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"2Q6c2XiYLx5m"},"source":["LR - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"vBcpnHOhLx5n","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750541637,"user_tz":180,"elapsed":26967,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"055a4da4-cf95-4404-95b0-af34d5ee707a"},"source":["y_pred = y_pred_lr\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":53,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.742525</td>\n","      <td>0.8</td>\n","      <td>0.66881</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision   Recall\n","0  0.742525        0.8  0.66881"]},"metadata":{"tags":[]},"execution_count":53}]},{"cell_type":"markdown","metadata":{"id":"0mKy9uNSLeHw"},"source":["LR - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"KkTvyTFxLeH0","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750542027,"user_tz":180,"elapsed":27352,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"7be67398-9297-4b64-e217-f40052d14d79"},"source":["plot_confusion_matrix(model_lr, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":54,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"cXb9S37eMUWM"},"source":["RL - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"1XnxPXcnMUWP","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750542375,"user_tz":180,"elapsed":27693,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"a9fa9222-8209-4769-bf71-79d5aa1e6f71"},"source":["hit_rates = cross_val_score(model_lr, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_lr = hit_rates"],"execution_count":55,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"KyDq0EFUL4P0"},"source":["### Decision Tree"]},{"cell_type":"code","metadata":{"id":"4swx4I3X4cx4","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750542379,"user_tz":180,"elapsed":27690,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"59abcefd-e7be-4ffa-ee30-4c40ca4700fa"},"source":["filename = 'best_model_dt.sav'\n","\n","if run_grid_search_dt == True:\n","  # Create the parameter grid\n","  # parameters in https://scikit-learn.org/stable/modules/tree.html#minimal-cost-complexity-pruning\n","\n","  param_grid = { \n","      'min_samples_leaf': [1, 10, 20, 40],\n","      'max_depth': [1, 6, 12],\n","      \n","      'criterion':['gini','entropy'],\n","      'splitter':['best', 'random'],\n","      'min_samples_split': [2, 5, 15, 20, 30]\n","      }\n","\n","  # Create a based model\n","  model_dt = DecisionTreeClassifier()\n","\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_dt, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = -1, verbose = 2,scoring = 'roc_auc')\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_dt = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_dt, open(filename, 'wb'))\n","  files.download(filename)\n","else:\n","  #load\n","  model_dt = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_dt)\n","y_pred_dt = model_dt.predict(X_test)\n","\n","#Fitting 10 folds for each of 800 candidates, totalling 8000 fits"],"execution_count":56,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='entropy',\n","                       max_depth=12, max_features=None, max_leaf_nodes=None,\n","                       min_impurity_decrease=0.0, min_impurity_split=None,\n","                       min_samples_leaf=40, min_samples_split=2,\n","                       min_weight_fraction_leaf=0.0, presort='deprecated',\n","                       random_state=None, splitter='random')\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"czAInE7bL4P4"},"source":["DT - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"Or3Fy56zL4P5","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750542380,"user_tz":180,"elapsed":27684,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"51696357-31a8-45a9-af57-339b9c01e6c2"},"source":["y_pred = y_pred_dt\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":57,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.715947</td>\n","      <td>0.759259</td>\n","      <td>0.659164</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.715947   0.759259  0.659164"]},"metadata":{"tags":[]},"execution_count":57}]},{"cell_type":"markdown","metadata":{"id":"jtRjvPYCL4P7"},"source":["DT - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"7pKJfxMwL4P8","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750542671,"user_tz":180,"elapsed":27968,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"a66da819-6d2b-416f-cd76-ecffb2235dfc"},"source":["plot_confusion_matrix(model_dt, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":58,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"nbd3quA0L4P-"},"source":["DT - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"Qhbpg-ZsL4P_","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750543000,"user_tz":180,"elapsed":28289,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"b54422dd-c09f-4b19-dc07-8c94e4d0cee2"},"source":["\n","hit_rates = cross_val_score(model_dt, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_dt = hit_rates"],"execution_count":59,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"nWYxOweyhZib"},"source":["### KNN"]},{"cell_type":"code","metadata":{"id":"67kH7wx-hZie","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750543001,"user_tz":180,"elapsed":28282,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"e34ddf0f-846a-4bc5-ed5e-2cdde9f924b5"},"source":["filename = 'best_model_knn.sav'\n","\n","if run_grid_search_knn == True:\n","  # Create the parameter grid\n","  \n","\n","  param_grid = { \n","      'leaf_size':[1, 10, 20, 40],\n","      'algorithm':['ball_tree', 'kd_tree', 'brute'],\n","      'metric': ['str', 'callable','minkowski'],\n","      'n_neighbors':[2,4,6,8,10,12,14,16]\n","      }\n","\n","  # Create a based model\n","  model_knn = KNeighborsClassifier()\n","\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_knn, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_knn = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_knn, open(filename, 'wb'))\n","  files.download(filename)\n","else:\n","  #load\n","  model_knn = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_knn)\n","y_pred_knn = model_knn.predict(X_test)\n","\n","#Fitting 10 folds for each of 800 candidates, totalling 8000 fits"],"execution_count":60,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","KNeighborsClassifier(algorithm='ball_tree', leaf_size=1, metric='minkowski',\n","                     metric_params=None, n_jobs=None, n_neighbors=8, p=2,\n","                     weights='uniform')\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"GTQ_qBPzhZij"},"source":[" KNN - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"zVn2y2nYhZij","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750543001,"user_tz":180,"elapsed":28272,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"29de0a9e-4fd5-4520-b0f7-c1a7a1d50bc5"},"source":["y_pred = y_pred_knn\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":61,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.686047</td>\n","      <td>0.827957</td>\n","      <td>0.495177</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.686047   0.827957  0.495177"]},"metadata":{"tags":[]},"execution_count":61}]},{"cell_type":"markdown","metadata":{"id":"Z4Nkg6PIhZim"},"source":["KNN - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"s0tcsQbBhZim","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750543301,"user_tz":180,"elapsed":28565,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"540bb3ba-0199-45d1-d5fe-f4b3ea03104d"},"source":["plot_confusion_matrix(model_knn, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":62,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"lATIpTGuhZio"},"source":["KNN - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"ZphQgIzChZiq","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750543895,"user_tz":180,"elapsed":29153,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"729d3a37-dc02-4a51-b6e8-e6eab92c962c"},"source":["\n","hit_rates = cross_val_score(model_knn, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_knn = hit_rates"],"execution_count":63,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"hqQgEHL9GR4f"},"source":["### Naive Bayes"]},{"cell_type":"code","metadata":{"id":"KcczC5Z5GR4g","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750543896,"user_tz":180,"elapsed":29143,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"fbf2c9a7-b387-43fc-bdfb-8fae69a23888"},"source":["filename = 'best_model_nb.sav'\n","\n","if run_grid_search_nb == True:\n","  # Create the parameter grid\n","  \n","\n","  param_grid = { \n","      'var_smoothing':[1e-5, 1e-7, 1e-9, 1e-10,1e-12]\n","        }\n","\n","  # Create a based model\n","  model_nb = GaussianNB()\n","\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_nb, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_nb = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_nb, open(filename, 'wb'))\n","  files.download(filename)\n","else:\n","  #load\n","  model_nb = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_nb)\n","y_pred_nb = model_nb.predict(X_test)\n","\n","#Fitting 10 folds for each of 800 candidates, totalling 8000 fits"],"execution_count":64,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","GaussianNB(priors=None, var_smoothing=1e-05)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"mFIYQysyGR4i"},"source":["NB - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"0sjqnL1lGR4j","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750543897,"user_tz":180,"elapsed":29134,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"5f17bac6-3faa-4a42-ec50-ad3488ddafcd"},"source":["y_pred = y_pred_nb\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":65,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.687708</td>\n","      <td>0.786047</td>\n","      <td>0.543408</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.687708   0.786047  0.543408"]},"metadata":{"tags":[]},"execution_count":65}]},{"cell_type":"markdown","metadata":{"id":"_xtdMe0FGR4k"},"source":["NB - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"2XCyIt4kGR4l","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750544388,"user_tz":180,"elapsed":29619,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"b661ca96-1a95-49bb-8bf6-d7d565be713f"},"source":["plot_confusion_matrix(model_nb, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":66,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"ndW9neqIGR4n"},"source":["NB - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"Ro7amGBQGR4n","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750544721,"user_tz":180,"elapsed":29947,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"010f46b8-7a4c-4ad9-d6e2-8248d7959a8b"},"source":["\n","hit_rates = cross_val_score(model_nb, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_nb = hit_rates"],"execution_count":67,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"4EUCpV4qN0ij"},"source":["### Neural Network"]},{"cell_type":"code","metadata":{"id":"1flXN9KnN0il","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750544722,"user_tz":180,"elapsed":29941,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"79e3f749-43ac-49e1-d958-61a5939c524e"},"source":["filename = 'best_model_nn.sav'\n","\n","if run_grid_search_nn == True:\n","  # Create the parameter grid\n","  #https://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html#sklearn.neural_network.MLPClassifier\n","\n","  param_grid = {\n","                'learning_rate':['constant', 'invscaling', 'adaptive'],\n","                'solver':['lbfgs', 'sgd', 'adam'],\n","                'activation':['identity', 'logistic', 'tanh', 'relu'],\n","                'max_iter': [200,300,400],\n","                'alpha': [0.0001,0.0003],\n","                'hidden_layer_sizes':[1,2,3,4,5]\n","                }\n","\n","  # Create a based model\n","  model_nn = MLPClassifier()\n","\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_nn, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_nn = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_nn, open(filename, 'wb'))\n","  files.download(filename)\n","else:\n","  #load\n","  model_nn = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_nn)\n","y_pred_nn = model_nn.predict(X_test)\n","\n","#Fitting 10 folds for each of 800 candidates, totalling 8000 fits"],"execution_count":68,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","MLPClassifier(activation='tanh', alpha=0.0003, batch_size='auto', beta_1=0.9,\n","              beta_2=0.999, early_stopping=False, epsilon=1e-08,\n","              hidden_layer_sizes=3, learning_rate='invscaling',\n","              learning_rate_init=0.001, max_fun=15000, max_iter=300,\n","              momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True,\n","              power_t=0.5, random_state=None, shuffle=True, solver='adam',\n","              tol=0.0001, validation_fraction=0.1, verbose=False,\n","              warm_start=False)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"P5Mi3EiIN0io"},"source":["NN - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"6gE_fzRaN0ip","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750544723,"user_tz":180,"elapsed":29917,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"d71d9e9c-d405-4a99-e75b-8540e8513800"},"source":["y_pred = y_pred_nn\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":69,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.742525</td>\n","      <td>0.786765</td>\n","      <td>0.688103</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.742525   0.786765  0.688103"]},"metadata":{"tags":[]},"execution_count":69}]},{"cell_type":"markdown","metadata":{"id":"OpUmX36JN0ir"},"source":["NN - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"cv6XEdm4N0is","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750545276,"user_tz":180,"elapsed":30461,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"f4c1fb0d-0295-4e52-a9ab-25b835315c84"},"source":["plot_confusion_matrix(model_nn, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":70,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"aVTqPscoN0iu"},"source":["NN - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"NdRw7UtXN0iu","colab":{"base_uri":"https://localhost:8080/","height":0},"executionInfo":{"status":"ok","timestamp":1613750549907,"user_tz":180,"elapsed":35084,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"78ea1d39-8a6c-4cc3-b5bd-3813fa416502"},"source":["\n","hit_rates = cross_val_score(model_nn, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_nn = hit_rates"],"execution_count":71,"outputs":[{"output_type":"stream","text":["Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n","Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n","Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n","Stochastic Optimizer: Maximum iterations (300) reached and the optimization hasn't converged yet.\n","`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"e0FcGZTonvzM"},"source":["### SVM"]},{"cell_type":"code","metadata":{"id":"iFPZf12tnvzP","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1613750549908,"user_tz":180,"elapsed":35078,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"55ebf753-7d5c-4867-84c0-de6df4789ef6"},"source":["filename = 'best_model_svm.sav'\n","\n","if run_grid_search_svm == True:\n","  # Create the parameter grid\n","\n","\n","  param_grid = {\n","        'C':[0.001, 0.01, 0.1, 1, 10],\n","        'kernel':['linear', 'poly', 'sigmoid'],\n","        'shrinking':[True, False],\n","        'degree':[1,2,3,4,5]\n","        }\n","\n","  # Create a based model\n","  model_svm = svm.SVC()\n","\n","  # Instantiate the grid search model\n","  grid_search = GridSearchCV(estimator = model_svm, param_grid = param_grid, \n","                            cv = StratifiedKFold(cv_grid_search), n_jobs = 3, verbose = 2,scoring = 'roc_auc')\n","\n","  # Fit the grid search to the data\n","  grid_search.fit(X_train, y_train)\n","  grid_search.best_params_\n","\n","  model_svm = grid_search.best_estimator_\n","  #save\n","  pickle.dump(model_svm, open(filename, 'wb'))\n","  files.download(filename)\n","else:\n","  #load\n","  model_svm = pickle.load(open(filename, 'rb'))\n","  \n","print('Parameters of best model:')\n","print(model_svm)\n","y_pred_svm = model_svm.predict(X_test)\n","\n"],"execution_count":72,"outputs":[{"output_type":"stream","text":["Parameters of best model:\n","SVC(C=10, break_ties=False, cache_size=200, class_weight=None, coef0=0.0,\n","    decision_function_shape='ovr', degree=1, gamma='scale', kernel='poly',\n","    max_iter=-1, probability=False, random_state=None, shrinking=True,\n","    tol=0.001, verbose=False)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"0qmc9gwKnvzU"},"source":["SVM - Accuracy, precision and recall"]},{"cell_type":"code","metadata":{"id":"YsPX95FvnvzU","colab":{"base_uri":"https://localhost:8080/","height":76},"executionInfo":{"status":"ok","timestamp":1613750549908,"user_tz":180,"elapsed":35072,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"54ef9d85-07f4-4b26-a1fd-b645189627ec"},"source":["y_pred = y_pred_svm\n","d = {'Accuracy': [accuracy_score(y_test, y_pred)],\n","     'Precision': [precision_score(y_test, y_pred)],\n","     'Recall': [recall_score(y_test, y_pred)]}\n","dataframe_analisys = pd.DataFrame(data=d)\n","dataframe_analisys"],"execution_count":73,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Accuracy</th>\n","      <th>Precision</th>\n","      <th>Recall</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0.742525</td>\n","      <td>0.822314</td>\n","      <td>0.639871</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Accuracy  Precision    Recall\n","0  0.742525   0.822314  0.639871"]},"metadata":{"tags":[]},"execution_count":73}]},{"cell_type":"markdown","metadata":{"id":"l7hbsW33nvzW"},"source":["SVM - Confusion matrix"]},{"cell_type":"code","metadata":{"id":"obY_-G7HnvzX","colab":{"base_uri":"https://localhost:8080/","height":285},"executionInfo":{"status":"ok","timestamp":1613750550217,"user_tz":180,"elapsed":35375,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"152fc1f2-b405-4aa0-953a-2ee05bedc652"},"source":["plot_confusion_matrix(model_svm, X_test, y_test,display_labels=['0','1'], cmap=plt.cm.Blues,normalize='true')\n","plt.show()"],"execution_count":74,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"8R3BUboMnvzY"},"source":["SVM - Statistical analysis"]},{"cell_type":"code","metadata":{"id":"g7NjaqjznvzZ","colab":{"base_uri":"https://localhost:8080/","height":303},"executionInfo":{"status":"ok","timestamp":1613750551053,"user_tz":180,"elapsed":36203,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"ca343650-9767-4786-9c19-5b14cdccfb54"},"source":["\n","hit_rates = cross_val_score(model_svm, X_train, y_train, cv=StratifiedKFold(crossvalidation),scoring = 'roc_auc')\n","\n","sns.distplot(hit_rates, hist=True, kde=True, \n","             bins=8, color = 'darkblue', \n","             hist_kws={'edgecolor':'black'},\n","             kde_kws={'linewidth': 4})\n","hit_rates_svm = hit_rates"],"execution_count":75,"outputs":[{"output_type":"stream","text":["`distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"wxtPbs-7rEXc"},"source":["## - Models comparation;\n"]},{"cell_type":"code","metadata":{"id":"b6Xb28u6rCsE","colab":{"base_uri":"https://localhost:8080/","height":735},"executionInfo":{"status":"ok","timestamp":1613750552935,"user_tz":180,"elapsed":38079,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"8ca8891c-cc73-45a8-f0e9-e6a140335946"},"source":["print('Density')\n","\n","dt_tmp = {\n","          'CB':hit_rates_cb,\n","          'DT':hit_rates_dt,\n","          'GB':hit_rates_gb,\n","          'LGBM':hit_rates_lgbm,\n","          'KNN':hit_rates_knn,\n","          'LR':hit_rates_lr,\n","          'NB':hit_rates_nb,\n","          'NN':hit_rates_nn,\n","          'RF':hit_rates_rf,\n","          'SVM':hit_rates_svm,\n","          'XGB':hit_rates_xgb\n","          }\n","\n","dt_tmp = pd.DataFrame(dt_tmp)\n","\n","fig, ax = plt.subplots(figsize=(8,6))\n","sns.kdeplot(data=dt_tmp,legend=True,bw_method=0.7)\n","\n","plt.show()\n","\n","a = [hit_rates_cb.tolist(),\n","     hit_rates_dt.tolist(),\n","     hit_rates_gb.tolist(), \n","     hit_rates_lgbm.tolist(),\n","     hit_rates_knn.tolist(), \n","     hit_rates_lr.tolist(),\n","     hit_rates_nb.tolist(),\n","     hit_rates_nn.tolist(),\n","     hit_rates_rf.tolist(),\n","     hit_rates_svm.tolist(),\n","     hit_rates_xgb.tolist()]\n","\n","\n","print('Friedman Test')\n","print(friedmanchisquare(*a))\n","posthoc = sp.posthoc_nemenyi_friedman(list(map(list, zip(*a))))\n","models_names = ['CB','DT','GB','LGBM','KNN','LR','NB','NN','RF','SVM','XGB']\n","fig, ax = plt.subplots(figsize=(8,5)) \n","ax = sns.heatmap(\n","    posthoc, vmin=0, \n","    vmax=1, xticklabels=models_names,\n","    yticklabels=models_names,\n","    cmap=\"Greens\",linewidths=.5,\n","    annot=True,fmt='.2f')\n","#plt.savefig('matrix.png')\n","plt.show()"],"execution_count":76,"outputs":[{"output_type":"stream","text":["Density\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x432 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Friedman Test\n","FriedmanchisquareResult(statistic=31.715399610136473, pvalue=0.0004465821712576912)\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x360 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"SPfWQZij-2QM","colab":{"base_uri":"https://localhost:8080/","height":753},"executionInfo":{"status":"ok","timestamp":1613750553973,"user_tz":180,"elapsed":39112,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"bbcafae6-1b2d-4793-bf56-99709737c535"},"source":["print('Density')\n","\n","dt_tmp = {\n","          'RF':hit_rates_rf,\n","          'LGBM':hit_rates_lgbm,\n","          'XGB':hit_rates_xgb\n","          }\n","\n","dt_tmp = pd.DataFrame(dt_tmp)\n","\n","fig, ax = plt.subplots(figsize=(8,6))\n","plt.xlabel('AUC score', fontsize=15)\n","plt.ylabel('Kernel Density Estimate', fontsize=15)\n","sns.kdeplot(data=dt_tmp,legend=True,bw_method=0.6)\n","\n","plt.show()\n","\n","a = [hit_rates_rf.tolist(),\n","     hit_rates_lgbm.tolist(),\n","     hit_rates_xgb.tolist(),\n","     hit_rates_nn.tolist(),\n","     hit_rates_lr.tolist(),\n","     hit_rates_svm.tolist(),\n","     hit_rates_cb.tolist(),\n","     hit_rates_gb.tolist(),\n","     hit_rates_dt.tolist(),\n","     hit_rates_nb.tolist(),\n","     hit_rates_knn.tolist()\n","    ]\n","\n","\n","print('Friedman Test')\n","print(friedmanchisquare(*a))\n","posthoc = sp.posthoc_nemenyi_friedman(list(map(list, zip(*a))))\n","models_names = ['RF','LGBM','XGB','NN','LR','SVM','CB','GB','DT','NB','KNN']\n","fig, ax = plt.subplots(figsize=(8,5)) \n","ax = sns.heatmap(\n","    posthoc, vmin=0, \n","    vmax=1, xticklabels=models_names,\n","    yticklabels=models_names,\n","    cmap=\"Greens\",linewidths=.5,\n","    annot=True,fmt='.2f')\n","#plt.savefig('matrix.png')\n","plt.show()"],"execution_count":77,"outputs":[{"output_type":"stream","text":["Density\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x432 with 1 Axes>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Friedman Test\n","FriedmanchisquareResult(statistic=31.715399610136473, pvalue=0.0004465821712576912)\n"],"name":"stdout"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x360 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"O4-R4gWaL4QB"},"source":["## - Information Gain (Global);"]},{"cell_type":"markdown","metadata":{"id":"SiAg3BO2L4QC"},"source":["Funções utilizadas"]},{"cell_type":"code","metadata":{"id":"xx4ZISErL4QC","executionInfo":{"status":"ok","timestamp":1613750553975,"user_tz":180,"elapsed":39108,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}}},"source":["\n","\n","\n","def entropy(target_col):\n","    \"\"\"\n","    Calculate the entropy of a dataset.\n","    The only parameter of this function is the target_col parameter which specifies the target column\n","    \"\"\"\n","    elements,counts = np.unique(target_col,return_counts = True)\n","    entropy = np.sum([(-counts[i]/np.sum(counts))*np.log2(counts[i]/np.sum(counts)) for i in range(len(elements))])\n","    return entropy\n","\n","\n","################### \n","    \n","###################\n","\n","\n","def InfoGain(data,split_attribute_name,target_name=\"class\"):\n","    \"\"\"\n","    Calculate the information gain of a dataset. This function takes three parameters:\n","    1. data = The dataset for whose feature the IG should be calculated\n","    2. split_attribute_name = the name of the feature for which the information gain should be calculated\n","    3. target_name = the name of the target feature. The default for this example is \"class\"\n","    \"\"\"    \n","    #Calculate the entropy of the total dataset\n","    total_entropy = entropy(data[target_name])\n","    \n","    ##Calculate the entropy of the dataset\n","    \n","    #Calculate the values and the corresponding counts for the split attribute \n","    vals,counts= np.unique(data[split_attribute_name],return_counts=True)\n","    \n","    #Calculate the weighted entropy\n","    Weighted_Entropy = np.sum([(counts[i]/np.sum(counts))*entropy(data.where(data[split_attribute_name]==vals[i]).dropna()[target_name]) for i in range(len(vals))])\n","    \n","    #Calculate the information gain\n","    Information_Gain = total_entropy - Weighted_Entropy\n","    return Information_Gain\n","\n"],"execution_count":78,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"-Oq3uJpJL4QF"},"source":["Ganho de Informação - Ranque de atributos"]},{"cell_type":"code","metadata":{"id":"rksZ2NPcL4QF","colab":{"base_uri":"https://localhost:8080/","height":317},"executionInfo":{"status":"ok","timestamp":1613750561810,"user_tz":180,"elapsed":46937,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"bc23f393-74f3-491d-c33f-d61c1ccf3b69"},"source":["#Extraindo ganho de informacao de atributos\n","information_gain = pd.Series([InfoGain(df,feature,y_feature_name) for feature in x_features_names], index=x_features_names).sort_values(ascending=False)\n","\n","df_Pred2Town_feature_rank['info_gain_ent'] = information_gain.index[:]\n","att_count = 20\n","sns.barplot(x=information_gain[0:att_count], y=information_gain.index[0:att_count], color = (0.1, 0.4, 0.7, 0.6)) #Criando bar plot\n","plt.xlabel('Ganho de Informação')\n","plt.ylabel('Atributos')\n","plt.title(\"Ganho de Informação por atributo\")\n","plt.legend()\n","plt.autoscale(enable=True, axis='both', tight=None)\n","plt.show()"],"execution_count":79,"outputs":[{"output_type":"stream","text":["No handles with labels found to put in legend.\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"GEA_Amce3LLT"},"source":[""]},{"cell_type":"markdown","metadata":{"id":"OJzj6kHML4QK"},"source":["## - Attribute importance (Global);"]},{"cell_type":"code","metadata":{"id":"O-DHk3aSL4QL","colab":{"base_uri":"https://localhost:8080/","height":317},"executionInfo":{"status":"ok","timestamp":1613750561815,"user_tz":180,"elapsed":46936,"user":{"displayName":"José Ribeiro","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GjPO_0DAsiModaBdwKHllVtLAqSc1LvOHFSqngMiw=s64","userId":"10789669540889156464"}},"outputId":"7c00550e-ee93-4f70-e4a1-f3ec9242364e"},"source":["\n","#Extracting importance from attributes of the Random Forest model\n","feature_imp = pd.Series(model_rf.feature_importances_,index=x_features_names).sort_values(ascending=False) \n","\n","df_Pred2Town_feature_rank['feat_imp_oob'] = feature_imp.index[:]\n","\n","sns.barplot(x=feature_imp[0:att_count], y=feature_imp.index[0:att_count], color = (0.1, 0.4, 0.7, 0.6)) #Criando bar plot\n","plt.xlabel('Importância de atributos')\n","plt.ylabel('Atributos')\n","plt.title(\"Importância por atributo\")\n","plt.autoscale(enable=True, axis='both', tight=None)\n","plt.legend()\n","plt.show()\n"],"execution_count":80,"outputs":[{"output_type":"stream","text":["No handles with labels found to put in legend.\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]}]}