DecisionTress.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yj59dKhVAODP",
        "outputId": "e4044df2-e5ac-4ba8-8471-9d2c4637473e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Decision Tree:\n",
            "Parameters: {'criterion': 'gini', 'max_depth': 5, 'random_state': 42, 'splitter': 'random'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "accuracy score: 0.5473372520874682\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "precision_macro score: 0.5440363908214219\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "recall_macro score: 0.5331093878144889\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "f1_macro score: 0.5090128368652571\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "accuracy score: 0.5457991333230157\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "precision_macro score: 0.5426650551874336\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "recall_macro score: 0.530440851325342\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[23689 60861]\n",
            " [20844 74606]]\n",
            "f1_macro score: 0.5017967764964029\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'gini', 'max_depth': 5, 'random_state': 42, 'splitter': 'best'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "accuracy score: 0.559399229355905\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "precision_macro score: 0.5886848125847701\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "recall_macro score: 0.5378632914789763\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "f1_macro score: 0.47277573109884824\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "accuracy score: 0.5599682772300577\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "precision_macro score: 0.5865395715025062\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "recall_macro score: 0.5393428178630026\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15232 69318]\n",
            " [ 9534 85916]]\n",
            "f1_macro score: 0.479653913152306\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'gini', 'max_depth': 10, 'random_state': 42, 'splitter': 'random'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "accuracy score: 0.5696326364429509\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "precision_macro score: 0.5709022784197337\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "recall_macro score: 0.5573377587519726\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "f1_macro score: 0.5416754188871613\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "accuracy score: 0.5689921485176411\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "precision_macro score: 0.5692277800607337\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "recall_macro score: 0.5574152846409384\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[27960 56590]\n",
            " [21765 73685]]\n",
            "f1_macro score: 0.5439024111126013\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'gini', 'max_depth': 10, 'random_state': 42, 'splitter': 'best'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "accuracy score: 0.5805089038474949\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "precision_macro score: 0.5821339473845508\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "recall_macro score: 0.5694219197928186\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "f1_macro score: 0.5578781694875949\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "accuracy score: 0.5799946232920007\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "precision_macro score: 0.5837343470132367\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "recall_macro score: 0.5676359073877844\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[30109 54441]\n",
            " [20511 74939]]\n",
            "f1_macro score: 0.55221003639179\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'gini', 'max_depth': 15, 'random_state': 42, 'splitter': 'random'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "accuracy score: 0.5777207880309233\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "precision_macro score: 0.5755794799856173\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "recall_macro score: 0.569913168252852\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "f1_macro score: 0.565385406980081\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "accuracy score: 0.5754564952587304\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "precision_macro score: 0.5732771147032726\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "recall_macro score: 0.5674163866737658\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[35510 49040]\n",
            " [27256 68194]]\n",
            "f1_macro score: 0.5623594058016039\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'gini', 'max_depth': 15, 'random_state': 42, 'splitter': 'best'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "accuracy score: 0.583401774114091\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "precision_macro score: 0.5821080819469578\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "recall_macro score: 0.5750376465431876\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "f1_macro score: 0.5697386567497567\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "accuracy score: 0.5840422679918525\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "precision_macro score: 0.5832352276745041\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "recall_macro score: 0.575420542999139\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37373 47177]\n",
            " [26958 68492]]\n",
            "f1_macro score: 0.5693977749496806\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 5, 'random_state': 42, 'splitter': 'random'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "accuracy score: 0.5473372520874682\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "precision_macro score: 0.5440363908214219\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "recall_macro score: 0.5331093878144889\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "f1_macro score: 0.5090128368652571\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "accuracy score: 0.5434872010381075\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "precision_macro score: 0.5398870842528145\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "recall_macro score: 0.5266016872056403\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[23315 61235]\n",
            " [20466 74984]]\n",
            "f1_macro score: 0.48802883738295016\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 5, 'random_state': 42, 'splitter': 'best'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "accuracy score: 0.5584230389647497\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "precision_macro score: 0.5940764947162642\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "recall_macro score: 0.536173439887013\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "f1_macro score: 0.46487998645912576\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "accuracy score: 0.5597087508127931\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "precision_macro score: 0.586540922430735\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "recall_macro score: 0.5390081030289068\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15231 69319]\n",
            " [ 9535 85915]]\n",
            "f1_macro score: 0.47875905193699275\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 10, 'random_state': 42, 'splitter': 'random'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "accuracy score: 0.5691921586368092\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "precision_macro score: 0.5683605280427126\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "recall_macro score: 0.5583894065816825\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "f1_macro score: 0.5472502806027136\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "accuracy score: 0.5694754833532598\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "precision_macro score: 0.5700094561210068\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "recall_macro score: 0.5577255886290936\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25227 59323]\n",
            " [17588 77862]]\n",
            "f1_macro score: 0.5437218245976482\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 10, 'random_state': 42, 'splitter': 'best'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "accuracy score: 0.5795017619824272\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "precision_macro score: 0.580282499095216\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "recall_macro score: 0.5689131037841589\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "f1_macro score: 0.5585771806701095\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "accuracy score: 0.5790279523452376\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "precision_macro score: 0.5819899389707262\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "recall_macro score: 0.5670038049366524\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[29620 54930]\n",
            " [20001 75449]]\n",
            "f1_macro score: 0.5524652728225321\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 15, 'random_state': 42, 'splitter': 'random'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "accuracy score: 0.5772993682464473\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "precision_macro score: 0.5755210945462299\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "recall_macro score: 0.5689783809379259\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "f1_macro score: 0.5634405263177894\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "accuracy score: 0.5761922052926934\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "precision_macro score: 0.5746316505747217\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "recall_macro score: 0.5672252307144743\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[33658 50892]\n",
            " [25069 70381]]\n",
            "f1_macro score: 0.5606063499053043\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 15, 'random_state': 42, 'splitter': 'best'}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "accuracy score: 0.5834113124079143\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "precision_macro score: 0.5824202887112501\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "recall_macro score: 0.5746934520645197\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "f1_macro score: 0.5687192530112906\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "accuracy score: 0.5851446660362737\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "precision_macro score: 0.5844449282576522\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "recall_macro score: 0.5764666249936854\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37128 47422]\n",
            " [26497 68953]]\n",
            "f1_macro score: 0.5704234672280577\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "Random Forest:\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 5, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "accuracy score: 0.5609920959943401\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "precision_macro score: 0.5874878695436966\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "recall_macro score: 0.5398451935743537\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "f1_macro score: 0.47847979622224057\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "accuracy score: 0.5641254653541794\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "precision_macro score: 0.5813501906984795\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "recall_macro score: 0.5452127919295904\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[17691 66859]\n",
            " [11688 83762]]\n",
            "f1_macro score: 0.49852885185023493\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 5, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "accuracy score: 0.5594706608752145\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "precision_macro score: 0.5952157451738783\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "recall_macro score: 0.5370320681307325\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "f1_macro score: 0.46521709211856355\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "accuracy score: 0.5616825857620754\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "precision_macro score: 0.5917983643705201\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "recall_macro score: 0.5401529273639344\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[12313 72237]\n",
            " [ 7040 88410]]\n",
            "f1_macro score: 0.4759982062015474\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 5, 'n_estimators': 15, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "accuracy score: 0.5603754294410533\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "precision_macro score: 0.6005565986077182\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "recall_macro score: 0.5376532199353835\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "f1_macro score: 0.4636302765518314\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "accuracy score: 0.5614135359321171\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "precision_macro score: 0.597543582470917\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "recall_macro score: 0.5392094867410162\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[12164 72386]\n",
            " [ 6827 88623]]\n",
            "f1_macro score: 0.4696552382163245\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 10, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "accuracy score: 0.5826898724984821\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "precision_macro score: 0.590903742275144\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "recall_macro score: 0.5686481265399633\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "f1_macro score: 0.5479660616159501\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "accuracy score: 0.5857541809171198\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "precision_macro score: 0.5953485151841307\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "recall_macro score: 0.5715968403051478\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25621 58929]\n",
            " [16158 79292]]\n",
            "f1_macro score: 0.5505232262031473\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 10, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "accuracy score: 0.5868875255317665\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "precision_macro score: 0.598824076964845\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "recall_macro score: 0.5720730292480735\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "f1_macro score: 0.548935682541046\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "accuracy score: 0.5881375315409083\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "precision_macro score: 0.6006164501243977\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "recall_macro score: 0.5733235071562734\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25697 58853]\n",
            " [15113 80337]]\n",
            "f1_macro score: 0.5501708760401536\n",
            "\n",
            "\n",
            "Parameters: {'criterion': 'entropy', 'max_depth': 10, 'n_estimators': 15, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "accuracy score: 0.5879756283946691\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "precision_macro score: 0.6015769352092014\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "recall_macro score: 0.5728024244262281\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "f1_macro score: 0.5483606880539387\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "accuracy score: 0.5886303964786428\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "precision_macro score: 0.603051973857886\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "recall_macro score: 0.5733339600901902\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[25206 59344]\n",
            " [14486 80964]]\n",
            "f1_macro score: 0.5483900434782442\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "XGBoost:\n",
            "Parameters: {'learning_rate': 0.01, 'max_depth': 5, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "accuracy score: 0.5615254393334614\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "precision_macro score: 0.5893564927545027\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "recall_macro score: 0.5404708433045378\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "f1_macro score: 0.47957603760015777\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "accuracy score: 0.5607325758980124\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "precision_macro score: 0.589623706376762\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "recall_macro score: 0.539446890039504\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15537 69013]\n",
            " [ 9684 85766]]\n",
            "f1_macro score: 0.4765798645243778\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.01, 'max_depth': 5, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "accuracy score: 0.5615444868674742\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "precision_macro score: 0.5893973982496534\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "recall_macro score: 0.5404919768762345\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "f1_macro score: 0.4796137891661722\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "accuracy score: 0.5608301946054913\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "precision_macro score: 0.5928372388272056\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "recall_macro score: 0.5392198648527875\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[15570 68980]\n",
            " [ 9718 85732]]\n",
            "f1_macro score: 0.4738331962643542\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.01, 'max_depth': 10, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "accuracy score: 0.5836255861889512\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "precision_macro score: 0.5875231680724582\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "recall_macro score: 0.57151716393765\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "f1_macro score: 0.5574158447517377\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "accuracy score: 0.5826041506729955\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "precision_macro score: 0.5860959276486113\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "recall_macro score: 0.5706095972016574\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[31914 52636]\n",
            " [21960 73490]]\n",
            "f1_macro score: 0.5567753626983014\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.01, 'max_depth': 10, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "accuracy score: 0.5879518216203254\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "precision_macro score: 0.5929015499513284\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "recall_macro score: 0.5757283446636627\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "f1_macro score: 0.5615905256245657\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "accuracy score: 0.5861898978672648\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "precision_macro score: 0.5906251881882396\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "recall_macro score: 0.5741193415966933\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[30535 54015]\n",
            " [20069 75381]]\n",
            "f1_macro score: 0.5602091880004405\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.01, 'max_depth': 15, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "accuracy score: 0.5876470433604936\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "precision_macro score: 0.5869936489341141\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "recall_macro score: 0.5790464795434541\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "f1_macro score: 0.57344440378866\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "accuracy score: 0.5875756270624537\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "precision_macro score: 0.5873407495817179\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "recall_macro score: 0.5787215889033767\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37229 47321]\n",
            " [26071 69379]]\n",
            "f1_macro score: 0.572444947584222\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.01, 'max_depth': 15, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "accuracy score: 0.5917351690411281\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "precision_macro score: 0.5915513176927234\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "recall_macro score: 0.5831182380483382\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "f1_macro score: 0.5775944248407018\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "accuracy score: 0.5913137425955751\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "precision_macro score: 0.591613581961514\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "recall_macro score: 0.5823778597089896\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37308 47242]\n",
            " [25694 69756]]\n",
            "f1_macro score: 0.5761458767520184\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.1, 'max_depth': 5, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "accuracy score: 0.5640183190672905\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "precision_macro score: 0.5970273516432807\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "recall_macro score: 0.5425323041360184\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "f1_macro score: 0.4791244517326227\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "accuracy score: 0.5645373654675028\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "precision_macro score: 0.5979164321054488\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "recall_macro score: 0.543109905011341\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[14913 69637]\n",
            " [ 8261 87189]]\n",
            "f1_macro score: 0.480075405260851\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.1, 'max_depth': 5, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "accuracy score: 0.5680683461084286\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "precision_macro score: 0.6023281135813029\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "recall_macro score: 0.5469793422597606\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "f1_macro score: 0.48723450578115096\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "accuracy score: 0.5687231067376652\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "precision_macro score: 0.6029050539272454\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "recall_macro score: 0.5477301486371402\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[16950 67600]\n",
            " [ 9360 86090]]\n",
            "f1_macro score: 0.4887451975687124\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.1, 'max_depth': 10, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "accuracy score: 0.5932090006740444\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "precision_macro score: 0.5990958051117001\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "recall_macro score: 0.5811094523234906\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "f1_macro score: 0.5675831182228919\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "accuracy score: 0.5931113756456284\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "precision_macro score: 0.5987795999970753\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "recall_macro score: 0.5810900525274134\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[31700 52850]\n",
            " [20123 75327]]\n",
            "f1_macro score: 0.5678111530176189\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.1, 'max_depth': 10, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "accuracy score: 0.5973590270915924\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "precision_macro score: 0.6041735061493934\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "recall_macro score: 0.5852659408460203\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "f1_macro score: 0.5719905592673223\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "accuracy score: 0.5984209399034797\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "precision_macro score: 0.605314375701642\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "recall_macro score: 0.5863898290369611\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[31906 52644]\n",
            " [19720 75730]]\n",
            "f1_macro score: 0.5733491701166886\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.1, 'max_depth': 15, 'n_estimators': 5, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "accuracy score: 0.598142368134768\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "precision_macro score: 0.5985211700259341\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "recall_macro score: 0.5896251004827154\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "f1_macro score: 0.5844366880315424\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "accuracy score: 0.5994042808616202\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "precision_macro score: 0.6000809875062074\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "recall_macro score: 0.5907886218414604\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[37388 47162]\n",
            " [24575 70875]]\n",
            "f1_macro score: 0.5854378935296989\n",
            "\n",
            "\n",
            "Parameters: {'learning_rate': 0.1, 'max_depth': 15, 'n_estimators': 10, 'random_state': 42}\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "accuracy score: 0.6056019435605526\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "precision_macro score: 0.6065062768892215\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "recall_macro score: 0.5972830430391298\n",
            "\n",
            "\n",
            "Cross-validation method: KFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "f1_macro score: 0.5926084067406492\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: accuracy\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "accuracy score: 0.6063281427953507\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: precision_macro\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "precision_macro score: 0.6073131814152923\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: recall_macro\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "recall_macro score: 0.598023242432155\n",
            "\n",
            "\n",
            "Cross-validation method: StratifiedKFold\n",
            "Scoring metric: f1_macro\n",
            "Confusion matrix: \n",
            "[[38744 45806]\n",
            " [24422 71028]]\n",
            "f1_macro score: 0.5933750966822994\n",
            "\n",
            "\n",
            "\n",
            "\n",
            "Saved Decision Tree best model\n",
            "Saved Random Forest best model\n",
            "Saved XGBoost best model\n",
            "\n",
            "\n",
            "Results:\n",
            "Decision Tree:\n",
            "CV method: KFold, Metric: accuracy, Score: 0.547337\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.544036\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.533109\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.509013\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.545799\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.542665\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.530441\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.501797\n",
            "CV method: KFold, Metric: accuracy, Score: 0.559399\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.588685\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.537863\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.472776\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.559968\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.586540\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.539343\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.479654\n",
            "CV method: KFold, Metric: accuracy, Score: 0.569633\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.570902\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.557338\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.541675\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.568992\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.569228\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.557415\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.543902\n",
            "CV method: KFold, Metric: accuracy, Score: 0.580509\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.582134\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.569422\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.557878\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.579995\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.583734\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.567636\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.552210\n",
            "CV method: KFold, Metric: accuracy, Score: 0.577721\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.575579\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.569913\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.565385\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.575456\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.573277\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.567416\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.562359\n",
            "CV method: KFold, Metric: accuracy, Score: 0.583402\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.582108\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.575038\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.569739\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.584042\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.583235\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.575421\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.569398\n",
            "CV method: KFold, Metric: accuracy, Score: 0.547337\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.544036\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.533109\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.509013\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.543487\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.539887\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.526602\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.488029\n",
            "CV method: KFold, Metric: accuracy, Score: 0.558423\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.594076\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.536173\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.464880\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.559709\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.586541\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.539008\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.478759\n",
            "CV method: KFold, Metric: accuracy, Score: 0.569192\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.568361\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.558389\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.547250\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.569475\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.570009\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.557726\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.543722\n",
            "CV method: KFold, Metric: accuracy, Score: 0.579502\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.580282\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.568913\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.558577\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.579028\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.581990\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.567004\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.552465\n",
            "CV method: KFold, Metric: accuracy, Score: 0.577299\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.575521\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.568978\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.563441\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.576192\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.574632\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.567225\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.560606\n",
            "CV method: KFold, Metric: accuracy, Score: 0.583411\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.582420\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.574693\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.568719\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.585145\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.584445\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.576467\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.570423\n",
            "Random Forest:\n",
            "CV method: KFold, Metric: accuracy, Score: 0.560992\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.587488\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.539845\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.478480\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.564125\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.581350\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.545213\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.498529\n",
            "CV method: KFold, Metric: accuracy, Score: 0.559471\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.595216\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.537032\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.465217\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.561683\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.591798\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.540153\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.475998\n",
            "CV method: KFold, Metric: accuracy, Score: 0.560375\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.600557\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.537653\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.463630\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.561414\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.597544\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.539209\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.469655\n",
            "CV method: KFold, Metric: accuracy, Score: 0.582690\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.590904\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.568648\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.547966\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.585754\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.595349\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.571597\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.550523\n",
            "CV method: KFold, Metric: accuracy, Score: 0.586888\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.598824\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.572073\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.548936\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.588138\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.600616\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.573324\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.550171\n",
            "CV method: KFold, Metric: accuracy, Score: 0.587976\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.601577\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.572802\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.548361\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.588630\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.603052\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.573334\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.548390\n",
            "XGBoost:\n",
            "CV method: KFold, Metric: accuracy, Score: 0.561525\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.589356\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.540471\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.479576\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.560733\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.589624\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.539447\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.476580\n",
            "CV method: KFold, Metric: accuracy, Score: 0.561544\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.589397\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.540492\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.479614\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.560830\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.592837\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.539220\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.473833\n",
            "CV method: KFold, Metric: accuracy, Score: 0.583626\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.587523\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.571517\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.557416\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.582604\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.586096\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.570610\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.556775\n",
            "CV method: KFold, Metric: accuracy, Score: 0.587952\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.592902\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.575728\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.561591\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.586190\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.590625\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.574119\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.560209\n",
            "CV method: KFold, Metric: accuracy, Score: 0.587647\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.586994\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.579046\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.573444\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.587576\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.587341\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.578722\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.572445\n",
            "CV method: KFold, Metric: accuracy, Score: 0.591735\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.591551\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.583118\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.577594\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.591314\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.591614\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.582378\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.576146\n",
            "CV method: KFold, Metric: accuracy, Score: 0.564018\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.597027\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.542532\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.479124\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.564537\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.597916\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.543110\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.480075\n",
            "CV method: KFold, Metric: accuracy, Score: 0.568068\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.602328\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.546979\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.487235\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.568723\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.602905\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.547730\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.488745\n",
            "CV method: KFold, Metric: accuracy, Score: 0.593209\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.599096\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.581109\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.567583\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.593111\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.598780\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.581090\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.567811\n",
            "CV method: KFold, Metric: accuracy, Score: 0.597359\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.604174\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.585266\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.571991\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.598421\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.605314\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.586390\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.573349\n",
            "CV method: KFold, Metric: accuracy, Score: 0.598142\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.598521\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.589625\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.584437\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.599404\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.600081\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.590789\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.585438\n",
            "CV method: KFold, Metric: accuracy, Score: 0.605602\n",
            "CV method: KFold, Metric: precision_macro, Score: 0.606506\n",
            "CV method: KFold, Metric: recall_macro, Score: 0.597283\n",
            "CV method: KFold, Metric: f1_macro, Score: 0.592608\n",
            "CV method: StratifiedKFold, Metric: accuracy, Score: 0.606328\n",
            "CV method: StratifiedKFold, Metric: precision_macro, Score: 0.607313\n",
            "CV method: StratifiedKFold, Metric: recall_macro, Score: 0.598023\n",
            "CV method: StratifiedKFold, Metric: f1_macro, Score: 0.593375\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split, GridSearchCV, KFold, StratifiedKFold, cross_val_score\n",
        "from sklearn.tree import DecisionTreeClassifier\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from xgboost import XGBClassifier\n",
        "from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.decomposition import PCA\n",
        "import pickle\n",
        "from sklearn.metrics import confusion_matrix\n",
        "\n",
        "# Load the Higgs dataset\n",
        "df = pd.read_csv('HIGGS_train.csv', header=None, low_memory=False)\n",
        "df.dropna(inplace=True)\n",
        "\n",
        "# Separate the target variable and features\n",
        "X = df.iloc[:, 1:]\n",
        "y = df.iloc[:, 0]\n",
        "\n",
        "\n",
        "# Dimensionality reduction\n",
        "pca = PCA(n_components=10, random_state=42)\n",
        "X_pca = pca.fit_transform(X)\n",
        "\n",
        "# Use a more efficient data structure\n",
        "X_pca = np.array(X_pca)\n",
        "y = np.array(y)\n",
        "\n",
        "# Preprocessing\n",
        "scaler = StandardScaler()\n",
        "X_scaled = scaler.fit_transform(X_pca)\n",
        "\n",
        "# Split the data into training and testing sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X_scaled, y, test_size=0.3, random_state=42)\n",
        "\n",
        "# Define decision tree parameters\n",
        "dt_params = {'max_depth': [5, 10 ,15],\n",
        "             'criterion': ['gini','entropy'],\n",
        "             'splitter': ['random','best'],\n",
        "             'random_state': [42]}\n",
        "\n",
        "# Define random forest parameters\n",
        "rf_params = {'n_estimators': [5, 10, 15],\n",
        "             'max_depth': [5, 10],\n",
        "             'criterion': ['entropy'],\n",
        "             'random_state': [42]}\n",
        "\n",
        "# Define XGBoost parameters\n",
        "xgb_params = {'max_depth': [5, 10, 15],\n",
        "              'learning_rate': [0.01, 0.1],\n",
        "              'n_estimators': [5, 10],\n",
        "              'random_state': [42]}\n",
        "\n",
        "# Define the different cross-validation methods\n",
        "kf = KFold(n_splits=5, shuffle=True, random_state=42)\n",
        "skf = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)\n",
        "\n",
        "results = {}\n",
        "best_models = {}\n",
        "\n",
        "for model_name, model, params in [('Decision Tree', DecisionTreeClassifier(), dt_params),\n",
        "                                  ('Random Forest', RandomForestClassifier(), rf_params),\n",
        "                                  ('XGBoost', XGBClassifier(), xgb_params)]:\n",
        "    model_results = []\n",
        "    print(f'{model_name}:')\n",
        "    for param_set in GridSearchCV(model, params, cv=skf, scoring='accuracy').fit(X_train, y_train).cv_results_['params']:\n",
        "        print(f'Parameters: {param_set}')\n",
        "        for cv_method in ['KFold', 'StratifiedKFold']:\n",
        "            if cv_method == 'KFold':\n",
        "                cv = kf\n",
        "            else:\n",
        "                cv = skf\n",
        "            for metric in ['accuracy', 'precision_macro', 'recall_macro', 'f1_macro']:\n",
        "                print(f'Cross-validation method: {cv_method}')\n",
        "                print(f'Scoring metric: {metric}')\n",
        "                scores = cross_val_score(model.set_params(**param_set), X_train, y_train, cv=cv, scoring=metric, n_jobs=-1)\n",
        "                model_results.append((cv_method, metric, scores.mean()))\n",
        "                \n",
        "                # Print the confusion matrix\n",
        "                clf = model.set_params(**param_set).fit(X_train, y_train)\n",
        "                y_pred = clf.predict(X_test)\n",
        "                cm = confusion_matrix(y_test, y_pred)\n",
        "                print(f'Confusion matrix: \\n{cm}')\n",
        "                \n",
        "                print(f'{metric} score: {scores.mean()}')\n",
        "                print(\"\\n\")\n",
        "        \n",
        "        # Save the best model for this category\n",
        "        if model_name not in best_models:\n",
        "            best_models[model_name] = model.set_params(**param_set)\n",
        "        else:\n",
        "            old_scores = cross_val_score(best_models[model_name], X_train, y_train, cv=skf, scoring='accuracy', n_jobs=-1)\n",
        "            new_scores = cross_val_score(model.set_params(**param_set), X_train, y_train, cv=skf, scoring='accuracy', n_jobs=-1)\n",
        "            if new_scores.mean() > old_scores.mean():\n",
        "                best_models[model_name] = model.set_params(**param_set)\n",
        "\n",
        "    results[model_name] = model_results\n",
        "    print('\\n')\n",
        "    \n",
        "# Save the best models using pickle\n",
        "for model_name, model in best_models.items():\n",
        "    with open(f'{model_name}_best_model.pkl', 'wb') as f:\n",
        "        pickle.dump(model, f)\n",
        "        print(f'Saved {model_name} best model')\n",
        "\n",
        "print('\\n')\n",
        "print('Results:')\n",
        "for model_name, model_results in results.items():\n",
        "    print(f'{model_name}:')\n",
        "    for cv_method, metric, score in model_results:\n",
        "        print(f'CV method: {cv_method}, Metric: {metric}, Score: {score:.6f}')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "50EpuJUeV62O"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "gpuClass": "standard",
    "accelerator": "TPU"
  },
  "nbformat": 4,
  "nbformat_minor": 0
}