code/scratch.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load packages and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from DecisionTreeClassifier import (\n",
    "    DecisionTreeClassifier as CustomDecisionTreeClassifier,\n",
    ")\n",
    "from RandomForestClassifier import (\n",
    "    RandomForestClassifier as CustomRandomForestClassifier,\n",
    ")\n",
    "from GradientBoostingClassifier import (\n",
    "    GradientBoostingClassifier as CustomGradientBoostingClassifier,\n",
    ")\n",
    "\n",
    "from rich import print\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.ensemble import RandomForestClassifier as SklearnRandomForestClassifier\n",
    "from sklearn.ensemble import (\n",
    "    GradientBoostingClassifier as SklearnGradientBoostingClassifier,\n",
    ")\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.tree import DecisionTreeClassifier as SklearnDecisionTreeClassifier\n",
    "from sklearn.tree import plot_tree as plot_sklearn_tree\n",
    "from utils import print_evaluation_metrics\n",
    "\n",
    "logging.basicConfig(level=logging.INFO)\n",
    "\n",
    "%load_ext rich\n",
    "%load_ext autoreload \n",
    "\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generated dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "\u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m800\u001b[0m, \u001b[1;36m30\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m200\u001b[0m, \u001b[1;36m30\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m800\u001b[0m,\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m200\u001b[0m,\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m"
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     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "X, y = make_classification(\n",
    "    n_samples=1000,\n",
    "    n_features=30,\n",
    "    n_classes=2,\n",
    "    n_clusters_per_class=1,\n",
    "    n_informative=15,\n",
    "    random_state=42\n",
    ")\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X, y, test_size=0.2, random_state=42\n",
    ")\n",
    "\n",
    "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "hyperparameters = {\n",
    "    \"max_depth\": 5,\n",
    "    \"min_samples_split\": 15,\n",
    "    \"max_features\": 7,\n",
    "    \"min_impurity_decrease\": 0.001,\n",
    "    \"random_state\": 42,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Decision Tree\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Custom implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = CustomDecisionTreeClassifier(\n",
    "    **hyperparameters,\n",
    "    debug=True,\n",
    ")\n",
    "\n",
    "clf.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "\u001b[1m<\u001b[0m\u001b[1;95mgraphviz.graphs.Digraph\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x000001941050E920\u001b[0m\u001b[1m>\u001b[0m"
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     "execution_count": 9,
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   "source": [
    "clf.visualize_tree()"
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  {
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   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "preds = clf.predict(X_test)"
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  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
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     "name": "stdout",
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     "text": [
      "Model: Custom Decision Tree Classifier\n",
      "DecisionTreeClassifier(max_depth=5, min_samples_split=15, max_features=7, min_impurity_decrease=0.001, is_regression=False, random_state=42)\n",
      "Accuracy: 0.86\n",
      "Precision: 0.86\n",
      "Recall: 0.8601440576230492\n",
      "F1: 0.8599859985998599\n",
      "Classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.85      0.87      0.86        98\n",
      "           1       0.87      0.85      0.86       102\n",
      "\n",
      "    accuracy                           0.86       200\n",
      "   macro avg       0.86      0.86      0.86       200\n",
      "weighted avg       0.86      0.86      0.86       200\n",
      "\n"
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"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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 72\u001b[0m\u001b[1;36m0x504\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt_metrics = print_evaluation_metrics(y_test, preds, clf, \"Custom Decision Tree Classifier\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scikit-learn implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=5, max_features=7,\n",
       "                       min_impurity_decrease=0.001, min_samples_split=15,\n",
       "                       random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeClassifier</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=5, max_features=7,\n",
       "                       min_impurity_decrease=0.001, min_samples_split=15,\n",
       "                       random_state=42)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeClassifier(criterion='entropy', max_depth=5, max_features=7,\n",
       "                       min_impurity_decrease=0.001, min_samples_split=15,\n",
       "                       random_state=42)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sklearn_clf = SklearnDecisionTreeClassifier(\n",
    "    **hyperparameters,\n",
    "    criterion=\"entropy\",\n",
    ")\n",
    "\n",
    "sklearn_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sklearn_preds = sklearn_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Sklearn Decision Tree Classifier\n",
      "DecisionTreeClassifier(criterion='entropy', max_depth=5, max_features=7,\n",
      "                       min_impurity_decrease=0.001, min_samples_split=15,\n",
      "                       random_state=42)\n",
      "Accuracy: 0.85\n",
      "Precision: 0.8518667201926937\n",
      "Recall: 0.8507402961184474\n",
      "F1: 0.8499399759903962\n",
      "Classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.82      0.89      0.85        98\n",
      "           1       0.88      0.81      0.85       102\n",
      "\n",
      "    accuracy                           0.85       200\n",
      "   macro avg       0.85      0.85      0.85       200\n",
      "weighted avg       0.85      0.85      0.85       200\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 72\u001b[0m\u001b[1;36m0x504\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn_dt_metrics = print_evaluation_metrics(\n",
    "    y_test, sklearn_preds, sklearn_clf, \"Sklearn Decision Tree Classifier\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 144\u001b[0m\u001b[1;36m0x720\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m1\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "sklearn_tree = plot_sklearn_tree(\n",
    "    sklearn_clf,\n",
    "    filled=True,\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Random Forest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Custom implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG:RandomForestClassifier:Fitting 100 trees...\n",
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 12 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done   1 tasks      | elapsed:   13.8s\n",
      "[Parallel(n_jobs=-1)]: Done   2 tasks      | elapsed:   14.1s\n",
      "[Parallel(n_jobs=-1)]: Done   3 tasks      | elapsed:   15.1s\n",
      "[Parallel(n_jobs=-1)]: Done   4 tasks      | elapsed:   15.4s\n",
      "[Parallel(n_jobs=-1)]: Done   5 tasks      | elapsed:   15.4s\n",
      "[Parallel(n_jobs=-1)]: Done   6 tasks      | elapsed:   15.6s\n",
      "[Parallel(n_jobs=-1)]: Done   7 tasks      | elapsed:   15.7s\n",
      "[Parallel(n_jobs=-1)]: Done   8 tasks      | elapsed:   16.1s\n",
      "[Parallel(n_jobs=-1)]: Done   9 tasks      | elapsed:   16.2s\n",
      "[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:   16.4s\n",
      "[Parallel(n_jobs=-1)]: Done  11 tasks      | elapsed:   17.8s\n",
      "[Parallel(n_jobs=-1)]: Done  12 tasks      | elapsed:   17.9s\n",
      "[Parallel(n_jobs=-1)]: Done  13 tasks      | elapsed:   21.2s\n",
      "[Parallel(n_jobs=-1)]: Done  14 tasks      | elapsed:   22.7s\n",
      "[Parallel(n_jobs=-1)]: Done  15 tasks      | elapsed:   23.2s\n",
      "[Parallel(n_jobs=-1)]: Done  16 tasks      | elapsed:   23.4s\n",
      "[Parallel(n_jobs=-1)]: Done  17 tasks      | elapsed:   24.2s\n",
      "[Parallel(n_jobs=-1)]: Done  18 tasks      | elapsed:   24.7s\n",
      "[Parallel(n_jobs=-1)]: Done  19 tasks      | elapsed:   24.8s\n",
      "[Parallel(n_jobs=-1)]: Done  20 tasks      | elapsed:   25.5s\n",
      "[Parallel(n_jobs=-1)]: Done  21 tasks      | elapsed:   26.0s\n",
      "[Parallel(n_jobs=-1)]: Done  22 tasks      | elapsed:   26.2s\n",
      "[Parallel(n_jobs=-1)]: Done  23 tasks      | elapsed:   26.3s\n",
      "[Parallel(n_jobs=-1)]: Done  24 tasks      | elapsed:   27.6s\n",
      "[Parallel(n_jobs=-1)]: Done  25 tasks      | elapsed:   29.9s\n",
      "[Parallel(n_jobs=-1)]: Done  26 tasks      | elapsed:   30.6s\n",
      "[Parallel(n_jobs=-1)]: Done  27 tasks      | elapsed:   31.4s\n",
      "[Parallel(n_jobs=-1)]: Done  28 tasks      | elapsed:   31.7s\n",
      "[Parallel(n_jobs=-1)]: Done  29 tasks      | elapsed:   32.5s\n",
      "[Parallel(n_jobs=-1)]: Done  30 tasks      | elapsed:   33.8s\n",
      "[Parallel(n_jobs=-1)]: Done  31 tasks      | elapsed:   33.8s\n",
      "[Parallel(n_jobs=-1)]: Done  32 tasks      | elapsed:   34.0s\n",
      "[Parallel(n_jobs=-1)]: Done  33 tasks      | elapsed:   34.1s\n",
      "[Parallel(n_jobs=-1)]: Done  34 tasks      | elapsed:   34.2s\n",
      "[Parallel(n_jobs=-1)]: Done  35 tasks      | elapsed:   36.4s\n",
      "[Parallel(n_jobs=-1)]: Done  36 tasks      | elapsed:   36.5s\n",
      "[Parallel(n_jobs=-1)]: Done  37 tasks      | elapsed:   37.8s\n",
      "[Parallel(n_jobs=-1)]: Done  38 tasks      | elapsed:   39.2s\n",
      "[Parallel(n_jobs=-1)]: Done  39 tasks      | elapsed:   39.5s\n",
      "[Parallel(n_jobs=-1)]: Done  40 tasks      | elapsed:   39.5s\n",
      "[Parallel(n_jobs=-1)]: Done  41 tasks      | elapsed:   40.0s\n",
      "[Parallel(n_jobs=-1)]: Done  42 tasks      | elapsed:   41.3s\n",
      "[Parallel(n_jobs=-1)]: Done  43 tasks      | elapsed:   41.4s\n",
      "[Parallel(n_jobs=-1)]: Done  44 tasks      | elapsed:   41.7s\n",
      "[Parallel(n_jobs=-1)]: Done  45 tasks      | elapsed:   42.0s\n",
      "[Parallel(n_jobs=-1)]: Done  46 tasks      | elapsed:   42.1s\n",
      "[Parallel(n_jobs=-1)]: Done  47 tasks      | elapsed:   43.7s\n",
      "[Parallel(n_jobs=-1)]: Done  48 tasks      | elapsed:   43.9s\n",
      "[Parallel(n_jobs=-1)]: Done  49 tasks      | elapsed:   45.3s\n",
      "[Parallel(n_jobs=-1)]: Done  50 tasks      | elapsed:   46.1s\n",
      "[Parallel(n_jobs=-1)]: Done  51 tasks      | elapsed:   46.2s\n",
      "[Parallel(n_jobs=-1)]: Done  52 tasks      | elapsed:   46.5s\n",
      "[Parallel(n_jobs=-1)]: Done  53 tasks      | elapsed:   46.8s\n",
      "[Parallel(n_jobs=-1)]: Done  54 tasks      | elapsed:   48.2s\n",
      "[Parallel(n_jobs=-1)]: Done  55 tasks      | elapsed:   48.4s\n",
      "[Parallel(n_jobs=-1)]: Done  56 tasks      | elapsed:   48.7s\n",
      "[Parallel(n_jobs=-1)]: Done  57 tasks      | elapsed:   49.1s\n",
      "[Parallel(n_jobs=-1)]: Done  58 tasks      | elapsed:   49.4s\n",
      "[Parallel(n_jobs=-1)]: Done  59 tasks      | elapsed:   50.6s\n",
      "[Parallel(n_jobs=-1)]: Done  60 tasks      | elapsed:   50.8s\n",
      "[Parallel(n_jobs=-1)]: Done  61 tasks      | elapsed:   52.6s\n",
      "[Parallel(n_jobs=-1)]: Done  62 tasks      | elapsed:   52.8s\n",
      "[Parallel(n_jobs=-1)]: Done  63 tasks      | elapsed:   53.2s\n",
      "[Parallel(n_jobs=-1)]: Done  64 tasks      | elapsed:   53.2s\n",
      "[Parallel(n_jobs=-1)]: Done  65 tasks      | elapsed:   54.1s\n",
      "[Parallel(n_jobs=-1)]: Done  66 tasks      | elapsed:   55.0s\n",
      "[Parallel(n_jobs=-1)]: Done  67 tasks      | elapsed:   55.4s\n",
      "[Parallel(n_jobs=-1)]: Done  68 tasks      | elapsed:   55.4s\n",
      "[Parallel(n_jobs=-1)]: Done  69 tasks      | elapsed:   55.7s\n",
      "[Parallel(n_jobs=-1)]: Done  70 tasks      | elapsed:   56.2s\n",
      "[Parallel(n_jobs=-1)]: Done  71 tasks      | elapsed:   57.1s\n",
      "[Parallel(n_jobs=-1)]: Done  72 tasks      | elapsed:   58.3s\n",
      "[Parallel(n_jobs=-1)]: Done  73 tasks      | elapsed:   59.9s\n",
      "[Parallel(n_jobs=-1)]: Done  74 tasks      | elapsed:  1.0min\n",
      "[Parallel(n_jobs=-1)]: Done  75 tasks      | elapsed:  1.0min\n",
      "[Parallel(n_jobs=-1)]: Done  76 tasks      | elapsed:  1.0min\n",
      "[Parallel(n_jobs=-1)]: Done  77 tasks      | elapsed:  1.0min\n",
      "[Parallel(n_jobs=-1)]: Done  87 out of 100 | elapsed:  1.1min remaining:   10.1s\n",
      "[Parallel(n_jobs=-1)]: Done  97 out of 100 | elapsed:  1.2min remaining:    2.2s\n",
      "[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed:  1.2min finished\n",
      "DEBUG:RandomForestClassifier:OOB Score: 0.93125\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">OOB Score: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.93125</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "OOB Score: \u001b[1;36m0.93125\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf_clf = CustomRandomForestClassifier(\n",
    "    n_estimators=100,\n",
    "    **hyperparameters,\n",
    "    debug=True,\n",
    "    n_jobs=-1,\n",
    "    verbose=11\n",
    ")\n",
    "\n",
    "rf_clf.fit(X_train, y_train)\n",
    "print(f\"OOB Score: {rf_clf.oob_score_}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG:RandomForestClassifier:Making predictions using 100 trees...\n"
     ]
    }
   ],
   "source": [
    "rf_preds = rf_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Custom Random Forest Classifier\n",
      "RandomForestClassifier(n_estimators=100, max_depth=5, min_samples_split=15, max_features=7, min_impurity_decrease=0.001, random_state=42)\n",
      "OOB Score: 0.93125\n",
      "Accuracy: 0.92\n",
      "Precision: 0.92\n",
      "Recall: 0.9201680672268908\n",
      "F1: 0.9199919991999201\n",
      "Classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.93      0.92        98\n",
      "           1       0.93      0.91      0.92       102\n",
      "\n",
      "    accuracy                           0.92       200\n",
      "   macro avg       0.92      0.92      0.92       200\n",
      "weighted avg       0.92      0.92      0.92       200\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9I2ISsFW7YUmSpLYl5bWKxpK4fBNYHBGfbt6fBPxHeyFJkiSt31gSl9MY3gnvrc37HwF/0lpEkiSpJ4Z6uB66W8ayc+5QRCwDnsXw+upnAEtG/5YkSRrvhiZSqyging28vjl+CSwGyMzDexOaJEnSk41WcfkJcCVwTGbeDhARp/YkKkmS1LoSJ+eOthz6WGA1cHlEfCYiZkGBv6EkSVqvEpdDbzBxycyvZubxwP7A5Qxv/79bRHwyIo7sUXySJElP6LgBXWb+NjPPzcxXAtOB6xleaSRJkgqWRNeOXhnLcugnNLvmDjaHJEkqWC9bPN0yli3/JUmSxoWNqrhIkqSJo8SKi4mLJEmVmmjLoSVJksYVKy6SJFVqqLyCi4mLJEm1KvFZRbaKJElSMay4SJJUqex3AJvAxEWSpEqVuBzaVpEkSSqGFRdJkio1FOVNzjVxkSSpUiXOcbFVJEmSimHFRZKkSpU4OdfERZKkSpW4c66tIkmSVAwrLpIkVarELf9NXCRJqpSriiRJklpkxUWSpEqVODnXxEWSpEqVuBzaVpEkSSqGFRdJkirl5FxJklSMoejeMRYRMSkiro+Irzfv946IZRFxe0QsjoitOo1h4iJJknrl3cAtI95/FDgjM/cFHgDmdxrAxEWSpEoNdfHoJCKmA68Azm7eB3AEcEHzkUXA3E7jmLhIklSpbiYuETEQEdeMOAaecruPA/+LP+Q5uwBrM/Ox5v1KYPdOMTs5V5IkbbbMHAQG13ctIo4B1mTmtRHx0s25j4mLJEmVyt5tQHco8KqIOBrYGtgROBPYKSImN1WX6cCqTgPZKpIkqVK9muOSmX+XmdMzcwZwPPDtzHwDcDnw2uZj84CLOsVs4iJJkvrlNOA9EXE7w3NeFnb6gq0iSZIq1Y8t/zPzO8B3mtcrgIM35vsmLpIkVcqdcyVJklpkxUWSpEqNdav+8cTERZKkSvVjjsvmslUkSZKKYcVFkqRKlVhxMXGRJKlSriqSJElqkRUXSZIq5aoiSZJUDOe4SJKkYjjHRZIkqUVWXCRJqtRQgTUXExdJkipV4hwXW0WSJKkYVlwkSapUeY0iExdJkqplq0iSJKlFVlwkSaqUO+dKkqRilLgc2laRJEkqhhUXSZIqVV69xcRFkqRquapIkiSpRVZcJEmqVImTc01cJEmqVHlpi60iSZJUECsukiRVqsTJuSYukiRVqsQ5LraKJElSMay4SJJUqfLqLSYukiRVq8Q5LraKJElSMay4SJJUqSywWWTiIklSpWwVSZIkPUVEbB0RP4yIGyNieUR8qDm/d0Qsi4jbI2JxRGzVaSwTF0mSKjVEdu3o4L+AIzLzBcCBwOyIOAT4KHBGZu4LPADM7zSQiYskSZXKLh6j3mfYb5q3WzZHAkcAFzTnFwFzO8Vs4iJJkjZbRAxExDUjjoGnXJ8UETcAa4BLgZ8BazPzseYjK4HdO93HybmSJFWqm1v+Z+YgMDjK9XXAgRGxE3AhsP+m3MfERZKkSvVjVVFmro2Iy4E/B3aKiMlN1WU6sKrT920Vqave8Y4TuOaaS7j22kt55ztP7Hc40oT2xfO/ytw3vpU5bziJLy6+EICzBr/Aq//n23jNvHfwllPex5r77u9zlBJExK5NpYWI2AZ4OXALcDnw2uZj84CLOo1l4qKuOeCAZ3PCCa/nsMNexcEHz+aoo2axzz579TssaUK6bcUdLLn4m5x39sdZsujfuOL7P+Sulb/ghDe8hgu/8EmWLPoELzn0v/PJz53b71A1jmUX/+tgGnB5RPwIuBq4NDO/DpwGvCcibgd2ARZ2GsjERV2z//77cvXVN/Dww79n3bp1XHnlMubOnd3vsKQJacUdd/O85+zHNltvzeTJkzjowOdx2RXfY/vttnviMw8//Hsi+hikxr2hLh6jycwfZeYLM/P5mfnczPxwc35FZh6cmftm5usy8786xWzioq5ZvvynHHroi5gyZSe22WZrZs8+nOnTn9nvsKQJad999uK6G5ez9sGHePj3v+fKH1zNPffeB8CZn/48s179Jr5xyeW8881v6nOkUnf1fHJuRJyQmZ/bwLUBYABg8uQpTJ68fU9j0+a59dbb+ed//hRf+9qX+N3vfseNNy5n3bp1/Q5LmpCeNWNPTnzD6xg49f1ss/XW7DdzH7bYYvjfou8+6W9490l/w2e+sJhzl3zN5EUbVOKzivpRcfnQhi5k5mBmHpSZB5m0lGnRosUceugxvPzlx7F27YPcdtvP+x2SNGG95pV/yfmfPYtF//YxdtxhB2bsOf1J14858nAu+873+hSdStCrVlE3tVJxaSbfrPcSMLWNe2p82HXXXbjvvvvZY49nMmfObF7yklf3OyRpwrr/gbXssvNOrL5nDUuv+B7nDJ7BnXevYq89hvfw+vaVP2DvvaZ3GEUqS1utoqnAXzL83IGRAvh+S/fUOHDeeZ9iypSdefTRRznllA/w4IMP9TskacI69X0fYe1DDzF58mTe/963s+MO2/OBf/w4d9y1ktgieOaf7MYH/vbkfoepcWwoy2sVRbYQdEQsBD6XmVet59q5mfnXncbYZpu9yvu/KU0AD919eb9DkKq15TP26ek6sDfudWzX/q790p1f6UnsrVRcMnODT3ccS9IiSZK0Pm75L0lSpbr5rKJeMXGRJKlSLoeWJElqkRUXSZIq1Y+nQ28uExdJkipV4hwXW0WSJKkYVlwkSapUiZNzTVwkSapUiXNcbBVJkqRiWHGRJKlSbTz2p20mLpIkVcpVRZIkSS2y4iJJUqVKnJxr4iJJUqVcDi1JkorhHBdJkqQWWXGRJKlSLoeWJEnFKHFyrq0iSZJUDCsukiRVylVFkiSpGK4qkiRJapEVF0mSKuWqIkmSVAxbRZIkSS2y4iJJUqVcVSRJkooxVOAcF1tFkiSpGCYukiRVKrt4jCYi9oiIyyPi5ohYHhHvbs5PiYhLI+K25ufOnWI2cZEkqVJDZNeODh4D3puZBwCHAO+IiAOABcDSzJwJLG3ej8rERZIktSozV2fmdc3rXwO3ALsDc4BFzccWAXM7jeXkXEmSKtXNfVwiYgAYGHFqMDMH1/O5GcALgWXA1Mxc3Vy6B5ja6T4mLpIkVaqbO+c2ScofJSojRcT2wBLglMx8KCJGfj8jomNAtookSVLrImJLhpOWczLzK83peyNiWnN9GrCm0zgmLpIkVapXk3NjuLSyELglM/9lxKWLgXnN63nARZ1itlUkSVKlerhz7qHAm4AfR8QNzbn3AacD50fEfOBO4LhOA5m4SJKkVmXmVUBs4PKsjRnLxEWSpEp1c3Jur5i4SJJUqW4uh+4VJ+dKkqRiWHGRJKlStookSVIxbBVJkiS1yIqLJEmV6uE+Ll1j4iJJUqWGCpzjYqtIkiQVw4qLJEmVslUkSZKKYatIkiSpRVZcJEmqlK0iSZJUDFtFkiRJLbLiIklSpWwVSZKkYtgqkiRJapEVF0mSKmWrSJIkFSNzqN8hbDRbRZIkqRhWXCRJqtSQrSJJklSKdFWRJElSe6y4SJJUKVtFkiSpGLaKJEmSWmTFRZKkSpW45b+JiyRJlSpx51xbRZIkqRhWXCRJqlSJk3NNXCRJqpTLoSVJUjFKrLg4x0WSJBXDioskSZUqcTm0FRdJkiqVmV07OomIz0bEmoi4acS5KRFxaUTc1vzcudM4Ji6SJKkXPg/Mfsq5BcDSzJwJLG3ej8rERZKkSg2RXTs6yczvAr96yuk5wKLm9SJgbqdxnOMiSVKlxsGqoqmZubp5fQ8wtdMXrLhIkqTNFhEDEXHNiGNgY76fw1lUx0zKioskSZXq5qqizBwEBjfya/dGxLTMXB0R04A1nb5gxUWSpEplF//bRBcD85rX84CLOn3BxEWSJLUuIs4DfgDsFxErI2I+cDrw8oi4DXhZ835UtookSapULzegy8zXb+DSrI0Zx8RFkqRKjYNVRRvNVpEkSSqGFRdJkiq1GZNq+8bERZKkStkqkiRJapEVF0mSKlVixcXERZKkSpWXttgqkiRJBYkSy0Qa/yJioHluhaQe8s+eJjorLmrLRj0VVFLX+GdPE5qJiyRJKoaJiyRJKoaJi9pij13qD//saUJzcq4kSSqGFRdJklQMExdJklQMExd1VUTMjohbI+L2iFjQ73ikWkTEZyNiTUTc1O9YpDaZuKhrImIS8AngKOAA4PURcUB/o5Kq8Xlgdr+DkNpm4qJuOhi4PTNXZOYjwJeBOX2OSapCZn4X+FW/45DaZuKibtoduHvE+5XNOUmSusLERZIkFcPERd20CthjxPvpzTlJkrrCxEXddDUwMyL2joitgOOBi/sckyRpAjFxUddk5mPAO4FvAbcA52fm8v5GJdUhIs4DfgDsFxErI2J+v2OS2uCW/5IkqRhWXCRJUjFMXCRJUjFMXCRJUjFMXCRJUjFMXCRJUjFMXKRCRcS6iLghIm6KiH+PiG03Y6zPR8Rrm9dnj/ZwzIh4aUT8j024xx0R8YxNjVGSwMRFKtnDmXlgZj4XeAR468iLETF5UwbNzDdn5s2jfOSlwEYnLpLUDSYu0sRwJbBvUw25MiIuBm6OiEkR8bGIuDoifhQRJwHEsH+NiFsj4jJgt8cHiojvRMRBzevZEXFdRNwYEUsjYgbDCdKpTbXnsIjYNSKWNPe4OiIObb67S0RcEhHLI+JsIHr8/0TSBLRJ/yKTNH40lZWjgG82p/4MeG5m/jwiBoAHM/NFEfE04HsRcQnwQmA/4ABgKnAz8NmnjLsr8Bngxc1YUzLzVxHxKeA3mflPzefOBc7IzKsiYk+Gd07+U+CDwFWZ+eGIeAXgTq6SNpuJi1SubSLihub1lcBChls4P8zMnzfnjwSe//j8FeDpwEzgxcB5mbkO+EVEfHs94x8CfPfxsTLzVxuI42XAARFPFFR2jIjtm3sc23z3GxHxwKb9mpL0ByYuUrkezswDR55okoffjjwFnJyZ33rK547uYhxbAIdk5u/XE4skdZVzXKSJ7VvA2yJiS4CIeHZEbAd8F/irZg7MNODw9Xz3P4EXR8TezXenNOd/Deww4nOXACc//iYiDmxefhf46+bcUcDO3fqlJNXLxEWa2M5meP7KdRFxE/BphiutFwK3Nde+wPBThZ8kM+8DBoCvRMSNwOLm0teAVz8+ORd4F3BQM/n3Zv6wuulDDCc+yxluGd3V0u8oqSI+HVqSJBXDioskSSqGiYskSSqGiYskSSqGiYskSSqGiYskSSqGiYskSSqGiYskSSrG/wc4IMPLVIbbSgAAAABJRU5ErkJggg==",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 72\u001b[0m\u001b[1;36m0x504\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf_metrics = print_evaluation_metrics(y_test, rf_preds, rf_clf, \"Custom Random Forest Classifier\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mgraphviz.graphs.Digraph\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x000001941290F0A0\u001b[0m\u001b[1m>\u001b[0m"
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_idx = np.random.randint(0, rf_clf.n_estimators)\n",
    "\n",
    "print(f\"Visualizing tree {tree_idx}...\")\n",
    "rf_clf.trees[tree_idx].visualize_tree()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scikit-learn implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 12 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done  26 tasks      | elapsed:    0.1s\n",
      "[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed:    0.5s finished\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">OOB Score: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.94875</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "OOB Score: \u001b[1;36m0.94875\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn_rf_clf = SklearnRandomForestClassifier(\n",
    "    n_estimators=100,\n",
    "    **hyperparameters,\n",
    "    oob_score=True,\n",
    "    criterion=\"entropy\",\n",
    "    n_jobs=-1,\n",
    "    verbose=1,\n",
    ")\n",
    "\n",
    "sklearn_rf_clf.fit(X_train, y_train)\n",
    "print(f\"OOB Score: {sklearn_rf_clf.oob_score_}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=12)]: Using backend ThreadingBackend with 12 concurrent workers.\n",
      "[Parallel(n_jobs=12)]: Done  26 tasks      | elapsed:    0.0s\n",
      "[Parallel(n_jobs=12)]: Done 100 out of 100 | elapsed:    0.0s finished\n"
     ]
    }
   ],
   "source": [
    "sklearn_rf_preds = sklearn_rf_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Scikit-Learn Random Forest Classifier\n",
      "RandomForestClassifier(criterion='entropy', max_depth=5, max_features=7,\n",
      "                       min_impurity_decrease=0.001, min_samples_split=15,\n",
      "                       n_jobs=-1, oob_score=True, random_state=42, verbose=1)\n",
      "OOB Score: 0.94875\n",
      "Accuracy: 0.945\n",
      "Precision: 0.9477265853412642\n",
      "Recall: 0.9442777110844338\n",
      "F1: 0.9448331201885705\n",
      "Classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      0.91      0.94        98\n",
      "           1       0.92      0.98      0.95       102\n",
      "\n",
      "    accuracy                           0.94       200\n",
      "   macro avg       0.95      0.94      0.94       200\n",
      "weighted avg       0.95      0.94      0.94       200\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 72\u001b[0m\u001b[1;36m0x504\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn_rf_metrics = print_evaluation_metrics(\n",
    "    y_test, sklearn_rf_preds, sklearn_rf_clf, \"Scikit-Learn Random Forest Classifier\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Visualizing tree <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">82</span><span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "Visualizing tree \u001b[1;36m82\u001b[0m\u001b[33m...\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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     "metadata": {},
     "output_type": "display_data"
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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 144\u001b[0m\u001b[1;36m0x720\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m1\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "print(f\"Visualizing tree {tree_idx}...\")\n",
    "sklearn_rf_tree = plot_sklearn_tree(\n",
    "    sklearn_rf_clf.estimators_[tree_idx],\n",
    "    filled=True,\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gradient Boosting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Custom implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "DEBUG:GradientBoostingClassifier:Training tree 1...\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 1...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 1: 0.6353\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 2...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 2: 0.5880\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 3...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 3: 0.5494\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 4...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 4: 0.5116\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 5...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 5: 0.4789\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 6...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 6: 0.4482\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 7...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 7: 0.4222\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 8...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 8: 0.3971\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 9: 0.3752\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 10: 0.3563\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 11...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 11: 0.3397\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 12: 0.3234\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 13: 0.3082\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 14: 0.2945\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 15...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 15: 0.2838\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 16: 0.2721\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 17: 0.2636\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 18: 0.2536\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 19: 0.2461\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 20: 0.2400\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 21: 0.2319\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 22: 0.2254\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 23: 0.2184\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 24: 0.2125\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 25: 0.2047\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 26: 0.2005\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 27: 0.1956\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 28: 0.1900\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 29: 0.1846\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 30: 0.1798\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 31: 0.1751\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 32: 0.1707\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 34: 0.1631\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 35: 0.1601\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 36: 0.1569\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 37: 0.1555\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 38: 0.1527\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 39: 0.1494\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 40: 0.1465\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 41: 0.1450\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 42: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 43...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 43: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 44...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 44: 0.1423\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 45: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 46...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 46: 0.1423\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 47: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 48...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 48: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 49...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 49: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 50...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 50: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 51...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 51: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 52...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 52: 0.1423\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 53: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 54...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 54: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 55...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 55: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 56...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 56: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 57...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 57: 0.1423\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 58: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 59...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 59: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 60...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 60: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 61...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 61: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 62...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 62: 0.1423\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 63...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 63: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 64: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 65...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 65: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 66: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 67...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 67: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 68: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 69: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 70...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 70: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 71: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 72...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 72: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 73...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 73: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 74: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 75: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 76...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 76: 0.1422\n",
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      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 77: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 78...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 78: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 79...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 79: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 80...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 80: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 81...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 81: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 82...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 82: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 83...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 83: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 84...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 84: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 85...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 85: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 86...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 86: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 87...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 87: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 88...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 88: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 89...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 89: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 90...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 90: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 91...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 91: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 92...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 92: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 93...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 93: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 94...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 94: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 95...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 95: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 96...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 96: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 97...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 97: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 98...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 98: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 99...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 99: 0.1422\n",
      "DEBUG:GradientBoostingClassifier:Fitting tree 100...\n",
      "DEBUG:GradientBoostingClassifier:Loss after fitting tree 100: 0.1422\n"
     ]
    }
   ],
   "source": [
    "gb_clf = CustomGradientBoostingClassifier(\n",
    "    n_estimators=100,\n",
    "    learning_rate=0.3,\n",
    "    **hyperparameters,\n",
    "    debug=True,\n",
    ")\n",
    "\n",
    "gb_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "gb_preds = gb_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Custom Gradient Boosting Classifier\n",
      "GradientBoostingClassifier(n_estimators=100, learning_rate=0.3, max_depth=5, min_samples_split=15, max_features=7, min_impurity_decrease=0.001, random_state=42)\n",
      "Accuracy: 0.92\n",
      "Precision: 0.92\n",
      "Recall: 0.9201680672268908\n",
      "F1: 0.9199919991999201\n",
      "Classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.93      0.92        98\n",
      "           1       0.93      0.91      0.92       102\n",
      "\n",
      "    accuracy                           0.92       200\n",
      "   macro avg       0.92      0.92      0.92       200\n",
      "weighted avg       0.92      0.92      0.92       200\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 72\u001b[0m\u001b[1;36m0x504\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gb_metrics = print_evaluation_metrics(\n",
    "    y_test, gb_preds, gb_clf, \"Custom Gradient Boosting Classifier\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Visualizing tree <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span><span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "Visualizing tree \u001b[1;36m29\u001b[0m\u001b[33m...\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
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     "metadata": {},
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       "\u001b[1m<\u001b[0m\u001b[1;95mgraphviz.graphs.Digraph\u001b[0m\u001b[39m object at \u001b[0m\u001b[1;36m0x000001941311FF10\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tree_idx = np.random.randint(0, gb_clf.n_estimators)\n",
    "\n",
    "print(f\"Visualizing tree {tree_idx}...\")\n",
    "gb_clf.trees[tree_idx].visualize_tree()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scikit-learn implementation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      Iter       Train Loss   Remaining Time \n",
      "         1           1.0242            0.43s\n",
      "         2           0.7794            0.48s\n",
      "         3           0.6391            0.82s\n",
      "         4           0.5171            0.61s\n",
      "         5           0.4320            0.78s\n",
      "         6           0.3555            0.89s\n",
      "         7           0.2981            0.75s\n",
      "         8           0.2487            0.84s\n",
      "         9           0.2036            0.74s\n",
      "        10           0.1743            0.80s\n",
      "        11           0.1520            0.84s\n",
      "        12           0.1289            0.76s\n",
      "        13           0.1107            0.80s\n",
      "        14           0.0962            0.74s\n",
      "        15           0.0849            0.77s\n",
      "        16           0.0746            0.71s\n",
      "        17           0.0664            0.74s\n",
      "        18           0.0600            0.69s\n",
      "        19           0.0522            0.74s\n",
      "        20           0.0453            0.73s\n",
      "        21           0.0405            0.69s\n",
      "        22           0.0349            0.70s\n",
      "        23           0.0301            0.66s\n",
      "        24           0.0268            0.68s\n",
      "        25           0.0233            0.64s\n",
      "        26           0.0204            0.65s\n",
      "        27           0.0183            0.66s\n",
      "        28           0.0158            0.63s\n",
      "        29           0.0145            0.64s\n",
      "        30           0.0136            0.61s\n",
      "        31           0.0127            0.61s\n",
      "        32           0.0116            0.59s\n",
      "        33           0.0108            0.56s\n",
      "        34           0.0108            0.54s\n",
      "        35           0.0108            0.51s\n",
      "        36           0.0106            0.52s\n",
      "        37           0.0106            0.50s\n",
      "        38           0.0106            0.48s\n",
      "        39           0.0102            0.46s\n",
      "        40           0.0098            0.46s\n",
      "        41           0.0093            0.44s\n",
      "        42           0.0093            0.43s\n",
      "        43           0.0090            0.43s\n",
      "        44           0.0090            0.41s\n",
      "        45           0.0090            0.40s\n",
      "        46           0.0090            0.38s\n",
      "        47           0.0090            0.37s\n",
      "        48           0.0090            0.37s\n",
      "        49           0.0090            0.35s\n",
      "        50           0.0090            0.34s\n",
      "        51           0.0090            0.33s\n",
      "        52           0.0090            0.31s\n",
      "        53           0.0090            0.30s\n",
      "        54           0.0090            0.30s\n",
      "        55           0.0090            0.29s\n",
      "        56           0.0090            0.28s\n",
      "        57           0.0090            0.27s\n",
      "        58           0.0090            0.26s\n",
      "        59           0.0090            0.25s\n",
      "        60           0.0090            0.25s\n",
      "        61           0.0090            0.24s\n",
      "        62           0.0090            0.23s\n",
      "        63           0.0090            0.22s\n",
      "        64           0.0090            0.21s\n",
      "        65           0.0090            0.21s\n",
      "        66           0.0090            0.20s\n",
      "        67           0.0090            0.19s\n",
      "        68           0.0090            0.18s\n",
      "        69           0.0090            0.17s\n",
      "        70           0.0090            0.17s\n",
      "        71           0.0090            0.16s\n",
      "        72           0.0090            0.16s\n",
      "        73           0.0090            0.15s\n",
      "        74           0.0090            0.14s\n",
      "        75           0.0090            0.13s\n",
      "        76           0.0090            0.13s\n",
      "        77           0.0090            0.13s\n",
      "        78           0.0090            0.12s\n",
      "        79           0.0090            0.11s\n",
      "        80           0.0090            0.10s\n",
      "        81           0.0090            0.10s\n",
      "        82           0.0090            0.10s\n",
      "        83           0.0090            0.09s\n",
      "        84           0.0090            0.08s\n",
      "        85           0.0090            0.08s\n",
      "        86           0.0090            0.07s\n",
      "        87           0.0090            0.07s\n",
      "        88           0.0090            0.06s\n",
      "        89           0.0090            0.06s\n",
      "        90           0.0090            0.05s\n",
      "        91           0.0090            0.05s\n",
      "        92           0.0090            0.04s\n",
      "        93           0.0090            0.04s\n",
      "        94           0.0090            0.03s\n",
      "        95           0.0090            0.02s\n",
      "        96           0.0090            0.02s\n",
      "        97           0.0090            0.01s\n",
      "        98           0.0090            0.01s\n",
      "        99           0.0090            0.00s\n",
      "       100           0.0090            0.00s\n"
     ]
    },
    {
     "data": {
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       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GradientBoostingClassifier(learning_rate=0.3, max_depth=5, max_features=7,\n",
       "                           min_impurity_decrease=0.001, min_samples_split=15,\n",
       "                           random_state=42, verbose=3)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GradientBoostingClassifier</label><div class=\"sk-toggleable__content\"><pre>GradientBoostingClassifier(learning_rate=0.3, max_depth=5, max_features=7,\n",
       "                           min_impurity_decrease=0.001, min_samples_split=15,\n",
       "                           random_state=42, verbose=3)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "GradientBoostingClassifier(learning_rate=0.3, max_depth=5, max_features=7,\n",
       "                           min_impurity_decrease=0.001, min_samples_split=15,\n",
       "                           random_state=42, verbose=3)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sklearn_gb_clf = SklearnGradientBoostingClassifier(\n",
    "    n_estimators=100,\n",
    "    learning_rate=0.3,\n",
    "    **hyperparameters,\n",
    "    verbose=3,\n",
    ")\n",
    "\n",
    "sklearn_gb_clf.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "gb_sklearn_preds = sklearn_gb_clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: Scikit-Learn Gradient Boosting Classifier\n",
      "GradientBoostingClassifier(learning_rate=0.3, max_depth=5, max_features=7,\n",
      "                           min_impurity_decrease=0.001, min_samples_split=15,\n",
      "                           random_state=42, verbose=3)\n",
      "Accuracy: 0.96\n",
      "Precision: 0.962157809983897\n",
      "Recall: 0.9593837535014006\n",
      "F1: 0.9598997493734336\n",
      "Classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      0.93      0.96        98\n",
      "           1       0.94      0.99      0.96       102\n",
      "\n",
      "    accuracy                           0.96       200\n",
      "   macro avg       0.96      0.96      0.96       200\n",
      "weighted avg       0.96      0.96      0.96       200\n",
      "\n"
     ]
    },
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 72\u001b[0m\u001b[1;36m0x504\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sklearn_gb_metrics = print_evaluation_metrics(\n",
    "    y_test,\n",
    "    gb_sklearn_preds,\n",
    "    sklearn_gb_clf,\n",
    "    \"Scikit-Learn Gradient Boosting Classifier\",\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Visualizing tree <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">29</span><span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "Visualizing tree \u001b[1;36m29\u001b[0m\u001b[33m...\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 144\u001b[0m\u001b[1;36m0x720\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m1\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "print(f\"Visualizing tree {tree_idx}...\")\n",
    "sklearn_gb_tree = plot_sklearn_tree(\n",
    "    sklearn_gb_clf.estimators_[tree_idx][0],\n",
    "    filled=True,\n",
    ")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>model</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>precision</th>\n",
       "      <th>recall</th>\n",
       "      <th>f1</th>\n",
       "      <th>confusion_matrix</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Custom Decision Tree Classifier</td>\n",
       "      <td>DecisionTreeClassifier(max_depth=5, min_sample...</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.860144</td>\n",
       "      <td>0.859986</td>\n",
       "      <td>[[85, 13], [15, 87]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Sklearn Decision Tree Classifier</td>\n",
       "      <td>DecisionTreeClassifier(criterion='entropy', ma...</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.851867</td>\n",
       "      <td>0.85074</td>\n",
       "      <td>0.84994</td>\n",
       "      <td>[[87, 11], [19, 83]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Custom Random Forest Classifier</td>\n",
       "      <td>RandomForestClassifier(n_estimators=100, max_d...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.920168</td>\n",
       "      <td>0.919992</td>\n",
       "      <td>[[91, 7], [9, 93]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Scikit-Learn Random Forest Classifier</td>\n",
       "      <td>(DecisionTreeClassifier(criterion='entropy', m...</td>\n",
       "      <td>0.945</td>\n",
       "      <td>0.947727</td>\n",
       "      <td>0.944278</td>\n",
       "      <td>0.944833</td>\n",
       "      <td>[[89, 9], [2, 100]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Custom Gradient Boosting Classifier</td>\n",
       "      <td>GradientBoostingClassifier(n_estimators=100, l...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.920168</td>\n",
       "      <td>0.919992</td>\n",
       "      <td>[[91, 7], [9, 93]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Scikit-Learn Gradient Boosting Classifier</td>\n",
       "      <td>([DecisionTreeRegressor(criterion='friedman_ms...</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.962158</td>\n",
       "      <td>0.959384</td>\n",
       "      <td>0.9599</td>\n",
       "      <td>[[91, 7], [1, 101]]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "\n",
       "                                        name  \\\n",
       "\u001b[1;36m0\u001b[0m            Custom Decision Tree Classifier   \n",
       "\u001b[1;36m1\u001b[0m           Sklearn Decision Tree Classifier   \n",
       "\u001b[1;36m2\u001b[0m            Custom Random Forest Classifier   \n",
       "\u001b[1;36m3\u001b[0m      Scikit-Learn Random Forest Classifier   \n",
       "\u001b[1;36m4\u001b[0m        Custom Gradient Boosting Classifier   \n",
       "\u001b[1;36m5\u001b[0m  Scikit-Learn Gradient Boosting Classifier   \n",
       "\n",
       "                                               model accuracy precision  \\\n",
       "\u001b[1;36m0\u001b[0m  \u001b[1;35mDecisionTreeClassifier\u001b[0m\u001b[1m(\u001b[0m\u001b[33mmax_depth\u001b[0m=\u001b[1;36m5\u001b[0m, min_sample\u001b[33m...\u001b[0m     \u001b[1;36m0.86\u001b[0m      \u001b[1;36m0.86\u001b[0m   \n",
       "\u001b[1;36m1\u001b[0m  \u001b[1;35mDecisionTreeClassifier\u001b[0m\u001b[1m(\u001b[0m\u001b[33mcriterion\u001b[0m=\u001b[32m'entropy'\u001b[0m, ma\u001b[33m...\u001b[0m     \u001b[1;36m0.85\u001b[0m  \u001b[1;36m0.851867\u001b[0m   \n",
       "\u001b[1;36m2\u001b[0m  \u001b[1;35mRandomForestClassifier\u001b[0m\u001b[1m(\u001b[0m\u001b[33mn_estimators\u001b[0m=\u001b[1;36m100\u001b[0m, max_d\u001b[33m...\u001b[0m     \u001b[1;36m0.92\u001b[0m      \u001b[1;36m0.92\u001b[0m   \n",
       "\u001b[1;36m3\u001b[0m  \u001b[1m(\u001b[0m\u001b[1;35mDecisionTreeClassifier\u001b[0m\u001b[1m(\u001b[0m\u001b[33mcriterion\u001b[0m=\u001b[32m'entropy'\u001b[0m, m\u001b[33m...\u001b[0m    \u001b[1;36m0.945\u001b[0m  \u001b[1;36m0.947727\u001b[0m   \n",
       "\u001b[1;36m4\u001b[0m  \u001b[1;35mGradientBoostingClassifier\u001b[0m\u001b[1m(\u001b[0m\u001b[33mn_estimators\u001b[0m=\u001b[1;36m100\u001b[0m, l\u001b[33m...\u001b[0m     \u001b[1;36m0.92\u001b[0m      \u001b[1;36m0.92\u001b[0m   \n",
       "\u001b[1;36m5\u001b[0m  \u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;35mDecisionTreeRegressor\u001b[0m\u001b[1m(\u001b[0m\u001b[33mcriterion\u001b[0m='friedman_ms\u001b[33m...\u001b[0m     \u001b[1;36m0.96\u001b[0m  \u001b[1;36m0.962158\u001b[0m   \n",
       "\n",
       "     recall        f1      confusion_matrix  \n",
       "\u001b[1;36m0\u001b[0m  \u001b[1;36m0.860144\u001b[0m  \u001b[1;36m0.859986\u001b[0m  \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m85\u001b[0m, \u001b[1;36m13\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m15\u001b[0m, \u001b[1;36m87\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m  \n",
       "\u001b[1;36m1\u001b[0m   \u001b[1;36m0.85074\u001b[0m   \u001b[1;36m0.84994\u001b[0m  \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m87\u001b[0m, \u001b[1;36m11\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m19\u001b[0m, \u001b[1;36m83\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m  \n",
       "\u001b[1;36m2\u001b[0m  \u001b[1;36m0.920168\u001b[0m  \u001b[1;36m0.919992\u001b[0m    \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m91\u001b[0m, \u001b[1;36m7\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m9\u001b[0m, \u001b[1;36m93\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m  \n",
       "\u001b[1;36m3\u001b[0m  \u001b[1;36m0.944278\u001b[0m  \u001b[1;36m0.944833\u001b[0m   \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m89\u001b[0m, \u001b[1;36m9\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m2\u001b[0m, \u001b[1;36m100\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m  \n",
       "\u001b[1;36m4\u001b[0m  \u001b[1;36m0.920168\u001b[0m  \u001b[1;36m0.919992\u001b[0m    \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m91\u001b[0m, \u001b[1;36m7\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m9\u001b[0m, \u001b[1;36m93\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m  \n",
       "\u001b[1;36m5\u001b[0m  \u001b[1;36m0.959384\u001b[0m    \u001b[1;36m0.9599\u001b[0m   \u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m91\u001b[0m, \u001b[1;36m7\u001b[0m\u001b[1m]\u001b[0m, \u001b[1m[\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m101\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparison = pd.DataFrame(\n",
    "    {\n",
    "        \"Custom Decision Tree\": dt_metrics,\n",
    "        \"Sklearn Decision Tree\": sklearn_dt_metrics,\n",
    "        \"Custom Random Forest\": rf_metrics,\n",
    "        \"Scikit-Learn Random Forest\": sklearn_rf_metrics,\n",
    "        \"Custom Gradient Boosting\": gb_metrics,\n",
    "        \"Scikit-Learn Gradient Boosting\": sklearn_gb_metrics,\n",
    "    }\n",
    ").T.reset_index(drop=True)\n",
    "\n",
    "\n",
    "comparison"
   ]
  }
 ],
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