2_PredictiveModels_NoPCA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This notebook is to explore Scania Dataset, impute the missing values and No dimensionality reduction\n",
    "\n",
    "**Yasmin Fathy <Fathy.Yasmin@gmail.com>**\n",
    "\n",
    "**Latest Updates: 28/08/2020**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "from pprint import pprint\n",
    "\n",
    "# to display fully (non-truncated) data-frame\n",
    "pd.set_option('display.max_rows', 500)\n",
    "pd.set_option('display.max_columns', 500)\n",
    "pd.set_option('display.width', 1000)\n",
    "#pd.set_option('display.max_colwidth', -1)\n",
    "\n",
    "#Setup to show all results in jupiter not only the last one:\n",
    "\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\" # revert to 'last_expr' to get only last results\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "%matplotlib inline\n",
    "from pprint import pprint\n",
    "\n",
    "import matplotlib as mpl\n",
    "#mpl.rcParams['figure.figsize'] = (20,20)\n",
    "font = {'family' : 'DejaVu Sans',\n",
    "        'weight' : 'normal',\n",
    "        'size'   : 16}\n",
    "mpl.rc('font', **font)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report, accuracy_score, confusion_matrix, roc_auc_score, precision_score, make_scorer,\\\n",
    "    recall_score, f1_score, precision_recall_curve, log_loss, cohen_kappa_score,roc_curve, auc\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "RANDOM_STATE = 42"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**APS Misclasification Cost Function**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def __perform_measure(y_actual, y_hat):\n",
    "        TP = 0\n",
    "        FP = 0\n",
    "        TN = 0\n",
    "        FN = 0\n",
    "        y_actual = list(y_actual)\n",
    "        y_hat = list(y_hat)\n",
    "        for i in range(len(y_hat)):\n",
    "            if y_actual[i] == y_hat[i] == 1:\n",
    "                TP += 1\n",
    "            if y_hat[i] == 1 and y_actual[i] != y_hat[i]:\n",
    "                FP += 1\n",
    "            if y_actual[i] == y_hat[i] == 0:\n",
    "                TN += 1\n",
    "            if y_hat[i] == 0 and y_actual[i] != y_hat[i]:\n",
    "                FN += 1\n",
    "\n",
    "        return [TP, FP, TN, FN]\n",
    "\n",
    "def custom_cost_fn_loss(y_actual, y_hat):\n",
    "        [TP, FP, TN, FN] = __perform_measure(y_actual, y_hat)\n",
    "        # print(len(list(y_actual)),\n",
    "        #       len(list(y_hat)))\n",
    "        # cm = confusion_matrix(list(y_actual), list(y_hat))\n",
    "        # print(len(cm))\n",
    "        # print(len(cm[0]))\n",
    "        # print(cm)\n",
    "        # FP = cm[0][1]\n",
    "        # FN = cm[1][0]\n",
    "        return (500 * FN) + (FP * 10)\n",
    "    \n",
    "APS_cost_fn = make_scorer(custom_cost_fn_loss, greater_is_better=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ML Model Evalution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **y** : original label in the testing-set\n",
    "- **y_predict**: predicted label from the ML algorithm\n",
    "- **y_predict_prob**: probability output of the algorithm about the minority class"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Plotting the precision, recall curve**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_precession_recall_curve(y, y_predict, alg_name):\n",
    "    fpr, tpr, thresholds = precision_recall_curve(y, y_predict)\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "\n",
    "\n",
    "    plt.figure()\n",
    "    plt.plot(fpr, tpr, color='red', label='Precision Recall curve (area = %0.2f)' % roc_auc)\n",
    "    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.title('Precision Recall curve  '+ str(alg_name))\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_roc_auc_curve(y, y_predict, alg_name):\n",
    "    fpr, tpr, thresholds = roc_curve(y, y_predict)\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "\n",
    "\n",
    "    plt.figure()\n",
    "    plt.plot(fpr, tpr, color='red', label='ROC curve (area = %0.2f)' % roc_auc)\n",
    "    plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.title('Receiver operating characteristic')\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluating the results using a set of metrics**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_evaluaiton(y, y_predict, alg_name):        \n",
    "            print(classification_report(y, list(y_predict)))\n",
    "            cm = confusion_matrix(y, list(y_predict))\n",
    "            print(cm)\n",
    "            print(\"Accuracy:\", accuracy_score(y, y_predict))\n",
    "            print(\"roc_auc_score:\", roc_auc_score(y, y_predict))\n",
    "            print(\"precision_score:\", precision_score(y, y_predict))\n",
    "            print(\"recall_score:\", recall_score(y, y_predict))\n",
    "            print(\"f1_score:\", f1_score(y, y_predict))\n",
    "            FP = cm[0][1]\n",
    "            FN = cm[1][0]\n",
    "            print(\"CM: FP\", FP)\n",
    "            print(\"CM: FN\", FN)\n",
    "            print(\"APS Cost = \", (500 * FN) + (FP * 10))\n",
    "            plot_precession_recall_curve(y, y_predict, alg_name)\n",
    "            plot_roc_auc_curve(y, y_predict, alg_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Finding the threshold that minimises the misclassification of the minority class i.e. class = 1 and apply the best threshold as post-processing steps**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_cut_off(y, y_predict_prob):\n",
    "    fpr, tpr, thresholds = precision_recall_curve(y, y_predict_prob)\n",
    "    min_cost = np.inf\n",
    "    best_threshold = 0.5\n",
    "    costs = []\n",
    "    for threshold in tqdm(thresholds):\n",
    "        #y_pred_threshold = np.where(scores > threshold, 0, 1)\n",
    "        y_pred_threshold = y_predict_prob > threshold\n",
    "        tn, fp, fn, tp = confusion_matrix(y, y_pred_threshold).ravel()\n",
    "        cost = 10*fp + 500*fn\n",
    "        costs.append(cost)\n",
    "        if cost < min_cost:\n",
    "            min_cost = cost\n",
    "            best_threshold = threshold\n",
    "    print(\"Best threshold: {:.4f}\".format(best_threshold))\n",
    "    print(\"Min cost: {:.2f}\".format(min_cost))\n",
    "    return best_threshold\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read training and testing files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data_dir =\"ScaniaDataset/dimReduction/\"\n",
    "# df_train = pd.read_csv(data_dir+\"pca_aps_mean_failure_train_set.csv\")\n",
    "# df_test =  pd.read_csv(data_dir+\"pca_aps_mean_failure_test_set.csv\")\n",
    "\n",
    "data_dir =\"ScaniaDataset/imputation/\"\n",
    "df_train = pd.read_csv(data_dir+\"imp_aps_mean_failure_training_set.csv\")\n",
    "df_test =  pd.read_csv(data_dir+\"imp_aps_mean_failure_test_set.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    59000\n",
       "1     1000\n",
       "Name: class, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0    15625\n",
       "1      375\n",
       "Name: class, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train[\"class\"].value_counts()\n",
    "\n",
    "df_test[\"class\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "      <td>0.000000</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.000979</td>\n",
       "      <td>0.034368</td>\n",
       "      <td>0.030469</td>\n",
       "      <td>0.021086</td>\n",
       "      <td>0.017480</td>\n",
       "      <td>0.252354</td>\n",
       "      <td>0.269627</td>\n",
       "      <td>0.228244</td>\n",
       "      <td>0.232853</td>\n",
       "      <td>0.216434</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.172130</td>\n",
       "      <td>0.027925</td>\n",
       "      <td>0.034739</td>\n",
       "      <td>0.034739</td>\n",
       "      <td>0.035415</td>\n",
       "      <td>0.043479</td>\n",
       "      <td>0.001693</td>\n",
       "      <td>0.446972</td>\n",
       "      <td>0.527780</td>\n",
       "      <td>0.041502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.050171</td>\n",
       "      <td>2.329835e-10</td>\n",
       "      <td>0.004486</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.037208</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.016536</td>\n",
       "      <td>0.000046</td>\n",
       "      <td>0.026223</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.001244</td>\n",
       "      <td>0.007709</td>\n",
       "      <td>0.027562</td>\n",
       "      <td>0.019164</td>\n",
       "      <td>0.002982</td>\n",
       "      <td>0.001486</td>\n",
       "      <td>4.417780e-05</td>\n",
       "      <td>2.562819e-08</td>\n",
       "      <td>0.000484</td>\n",
       "      <td>0.034739</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.012483</td>\n",
       "      <td>0.002794</td>\n",
       "      <td>5.815179e-03</td>\n",
       "      <td>0.012301</td>\n",
       "      <td>0.005728</td>\n",
       "      <td>0.010592</td>\n",
       "      <td>0.012140</td>\n",
       "      <td>0.002044</td>\n",
       "      <td>0.000074</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000584</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.050517</td>\n",
       "      <td>0.001163</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.780107e-02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001868</td>\n",
       "      <td>0.044143</td>\n",
       "      <td>0.010630</td>\n",
       "      <td>0.006391</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.021296</td>\n",
       "      <td>0.045829</td>\n",
       "      <td>0.094192</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.040779</td>\n",
       "      <td>0.057779</td>\n",
       "      <td>0.032041</td>\n",
       "      <td>0.014773</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002118</td>\n",
       "      <td>0.023069</td>\n",
       "      <td>0.032751</td>\n",
       "      <td>0.012881</td>\n",
       "      <td>0.017378</td>\n",
       "      <td>0.015918</td>\n",
       "      <td>0.013067</td>\n",
       "      <td>7.421784e-03</td>\n",
       "      <td>8.179508e-03</td>\n",
       "      <td>1.073013e-02</td>\n",
       "      <td>0.001321</td>\n",
       "      <td>0.003800</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.012036</td>\n",
       "      <td>0.003496</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.220573e-05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.003646</td>\n",
       "      <td>0.018302</td>\n",
       "      <td>0.008157</td>\n",
       "      <td>0.001787</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.018766</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.018180</td>\n",
       "      <td>0.017407</td>\n",
       "      <td>0.013917</td>\n",
       "      <td>0.013244</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000572</td>\n",
       "      <td>0.006052</td>\n",
       "      <td>0.004078</td>\n",
       "      <td>0.000952</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000725</td>\n",
       "      <td>0.001724</td>\n",
       "      <td>9.689357e-04</td>\n",
       "      <td>0.000287</td>\n",
       "      <td>8.208840e-03</td>\n",
       "      <td>0.004005</td>\n",
       "      <td>2.279950e-04</td>\n",
       "      <td>1.532245e-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005920</td>\n",
       "      <td>0.003845</td>\n",
       "      <td>0.003575</td>\n",
       "      <td>0.004178</td>\n",
       "      <td>0.005457</td>\n",
       "      <td>0.007219</td>\n",
       "      <td>0.008733</td>\n",
       "      <td>0.016044</td>\n",
       "      <td>0.002785</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.018907</td>\n",
       "      <td>0.000217</td>\n",
       "      <td>0.001481</td>\n",
       "      <td>0.000449</td>\n",
       "      <td>0.006856</td>\n",
       "      <td>0.018766</td>\n",
       "      <td>0.015318</td>\n",
       "      <td>0.015317</td>\n",
       "      <td>0.008575</td>\n",
       "      <td>0.260487</td>\n",
       "      <td>0.274495</td>\n",
       "      <td>0.279667</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.006459</td>\n",
       "      <td>0.012036</td>\n",
       "      <td>0.018907</td>\n",
       "      <td>0.018907</td>\n",
       "      <td>0.019221</td>\n",
       "      <td>0.017698</td>\n",
       "      <td>0.006416</td>\n",
       "      <td>0.955934</td>\n",
       "      <td>0.005705</td>\n",
       "      <td>0.019802</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.215927e-05</td>\n",
       "      <td>0.004277</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>0.016250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.011610</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.494771e-07</td>\n",
       "      <td>0.001039</td>\n",
       "      <td>0.006944</td>\n",
       "      <td>0.010922</td>\n",
       "      <td>0.004667</td>\n",
       "      <td>0.001095</td>\n",
       "      <td>0.000688</td>\n",
       "      <td>1.538530e-06</td>\n",
       "      <td>2.219349e-05</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.018907</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.007340</td>\n",
       "      <td>0.001814</td>\n",
       "      <td>3.577230e-03</td>\n",
       "      <td>0.008252</td>\n",
       "      <td>0.003646</td>\n",
       "      <td>0.004847</td>\n",
       "      <td>0.004085</td>\n",
       "      <td>0.000710</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000823</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.023635</td>\n",
       "      <td>0.007970</td>\n",
       "      <td>0.000294</td>\n",
       "      <td>1.011367e-03</td>\n",
       "      <td>0.000352</td>\n",
       "      <td>0.001392</td>\n",
       "      <td>0.018224</td>\n",
       "      <td>0.007440</td>\n",
       "      <td>0.002963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.011535</td>\n",
       "      <td>0.019709</td>\n",
       "      <td>0.017052</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.020787</td>\n",
       "      <td>0.024761</td>\n",
       "      <td>0.009800</td>\n",
       "      <td>0.006837</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002630</td>\n",
       "      <td>0.020862</td>\n",
       "      <td>0.028186</td>\n",
       "      <td>0.008862</td>\n",
       "      <td>0.008391</td>\n",
       "      <td>0.005407</td>\n",
       "      <td>0.004716</td>\n",
       "      <td>3.019031e-03</td>\n",
       "      <td>4.272917e-03</td>\n",
       "      <td>4.228511e-03</td>\n",
       "      <td>0.000679</td>\n",
       "      <td>0.005064</td>\n",
       "      <td>0.000394</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.014942</td>\n",
       "      <td>0.003496</td>\n",
       "      <td>1.070067e-07</td>\n",
       "      <td>1.164918e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.002068</td>\n",
       "      <td>0.020031</td>\n",
       "      <td>0.004624</td>\n",
       "      <td>0.000679</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.016622</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.016839</td>\n",
       "      <td>0.017787</td>\n",
       "      <td>0.003860</td>\n",
       "      <td>0.006013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>0.000943</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006817</td>\n",
       "      <td>0.000490</td>\n",
       "      <td>0.013870</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>0.000255</td>\n",
       "      <td>8.637144e-05</td>\n",
       "      <td>0.000751</td>\n",
       "      <td>1.472287e-02</td>\n",
       "      <td>0.001519</td>\n",
       "      <td>5.264043e-07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003395</td>\n",
       "      <td>0.005779</td>\n",
       "      <td>0.005955</td>\n",
       "      <td>0.006902</td>\n",
       "      <td>0.007536</td>\n",
       "      <td>0.007068</td>\n",
       "      <td>0.005451</td>\n",
       "      <td>0.005705</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013861</td>\n",
       "      <td>0.000322</td>\n",
       "      <td>0.000659</td>\n",
       "      <td>0.000711</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>0.016622</td>\n",
       "      <td>0.009000</td>\n",
       "      <td>0.003564</td>\n",
       "      <td>0.003055</td>\n",
       "      <td>0.104646</td>\n",
       "      <td>0.099672</td>\n",
       "      <td>0.304878</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.026995</td>\n",
       "      <td>0.014942</td>\n",
       "      <td>0.013861</td>\n",
       "      <td>0.013861</td>\n",
       "      <td>0.014372</td>\n",
       "      <td>0.015408</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.185489</td>\n",
       "      <td>0.205238</td>\n",
       "      <td>0.017230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.012903</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.005794</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.016475</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.004260</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000350</td>\n",
       "      <td>0.007154</td>\n",
       "      <td>0.009360</td>\n",
       "      <td>0.002726</td>\n",
       "      <td>0.000310</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>7.692651e-07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.013861</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.004271</td>\n",
       "      <td>0.001139</td>\n",
       "      <td>1.222976e-03</td>\n",
       "      <td>0.003529</td>\n",
       "      <td>0.001340</td>\n",
       "      <td>0.004602</td>\n",
       "      <td>0.006622</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>0.000155</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.000398</td>\n",
       "      <td>0.026719</td>\n",
       "      <td>0.000662</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>1.062092e-03</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.019386</td>\n",
       "      <td>0.003356</td>\n",
       "      <td>0.000863</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.004745</td>\n",
       "      <td>0.020369</td>\n",
       "      <td>0.023377</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013231</td>\n",
       "      <td>0.016047</td>\n",
       "      <td>0.000652</td>\n",
       "      <td>0.000378</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000787</td>\n",
       "      <td>0.009608</td>\n",
       "      <td>0.012318</td>\n",
       "      <td>0.003494</td>\n",
       "      <td>0.004616</td>\n",
       "      <td>0.003559</td>\n",
       "      <td>0.004232</td>\n",
       "      <td>4.364196e-03</td>\n",
       "      <td>7.130884e-03</td>\n",
       "      <td>1.014768e-02</td>\n",
       "      <td>0.001321</td>\n",
       "      <td>0.004937</td>\n",
       "      <td>0.000135</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.285295e-08</td>\n",
       "      <td>7.688457e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.00007</td>\n",
       "      <td>0.000072</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>0.000138</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>4.220103e-07</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>6.176496e-07</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>3.712698e-05</td>\n",
       "      <td>4.320932e-05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.213954</td>\n",
       "      <td>0.245177</td>\n",
       "      <td>0.304878</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.010200</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000116</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.016485</td>\n",
       "      <td>0.017693</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>2.329835e-10</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>4.348078e-05</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.329835e-10</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001230</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>5.207662e-07</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000152</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.264183e-07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>0.000352</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.170718e-07</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000652</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>5.970003e-07</td>\n",
       "      <td>7.660803e-07</td>\n",
       "      <td>3.163775e-07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008299</td>\n",
       "      <td>0.027923</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.022164</td>\n",
       "      <td>0.003496</td>\n",
       "      <td>6.420405e-07</td>\n",
       "      <td>5.335323e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.010975</td>\n",
       "      <td>0.019148</td>\n",
       "      <td>0.002078</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.026587</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.022935</td>\n",
       "      <td>0.021431</td>\n",
       "      <td>0.013577</td>\n",
       "      <td>0.021556</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002251</td>\n",
       "      <td>0.005504</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001052</td>\n",
       "      <td>0.002979</td>\n",
       "      <td>0.016674</td>\n",
       "      <td>0.001674</td>\n",
       "      <td>0.005586</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>3.952830e-05</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>2.453857e-04</td>\n",
       "      <td>0.008361</td>\n",
       "      <td>2.486486e-05</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005791</td>\n",
       "      <td>0.008906</td>\n",
       "      <td>0.006070</td>\n",
       "      <td>0.006405</td>\n",
       "      <td>0.007245</td>\n",
       "      <td>0.007902</td>\n",
       "      <td>0.008593</td>\n",
       "      <td>0.032891</td>\n",
       "      <td>0.000617</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022239</td>\n",
       "      <td>0.001129</td>\n",
       "      <td>0.001814</td>\n",
       "      <td>0.000792</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.026587</td>\n",
       "      <td>0.027012</td>\n",
       "      <td>0.014547</td>\n",
       "      <td>0.008733</td>\n",
       "      <td>0.234058</td>\n",
       "      <td>0.215579</td>\n",
       "      <td>0.209186</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.182214</td>\n",
       "      <td>0.022164</td>\n",
       "      <td>0.022239</td>\n",
       "      <td>0.022239</td>\n",
       "      <td>0.022984</td>\n",
       "      <td>0.024743</td>\n",
       "      <td>0.000421</td>\n",
       "      <td>0.511293</td>\n",
       "      <td>0.541289</td>\n",
       "      <td>0.026558</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.027652</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.007103</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025291</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.006840</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010168</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.084575e-06</td>\n",
       "      <td>0.003989</td>\n",
       "      <td>0.014700</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.000891</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>0.000368</td>\n",
       "      <td>2.362743e-06</td>\n",
       "      <td>2.353134e-08</td>\n",
       "      <td>0.000427</td>\n",
       "      <td>0.022239</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.004697</td>\n",
       "      <td>0.001185</td>\n",
       "      <td>1.756501e-03</td>\n",
       "      <td>0.005359</td>\n",
       "      <td>0.002488</td>\n",
       "      <td>0.006035</td>\n",
       "      <td>0.015422</td>\n",
       "      <td>0.001725</td>\n",
       "      <td>0.000129</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001885</td>\n",
       "      <td>0.002268</td>\n",
       "      <td>0.042155</td>\n",
       "      <td>0.004893</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.224829e-04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.029729</td>\n",
       "      <td>0.004551</td>\n",
       "      <td>0.002520</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.015368</td>\n",
       "      <td>0.033420</td>\n",
       "      <td>0.033052</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.030069</td>\n",
       "      <td>0.053553</td>\n",
       "      <td>0.000993</td>\n",
       "      <td>0.000634</td>\n",
       "      <td>0.000860</td>\n",
       "      <td>0.007273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.016010</td>\n",
       "      <td>0.010527</td>\n",
       "      <td>0.014202</td>\n",
       "      <td>0.005398</td>\n",
       "      <td>0.009206</td>\n",
       "      <td>0.007981</td>\n",
       "      <td>0.006086</td>\n",
       "      <td>4.171776e-03</td>\n",
       "      <td>6.044861e-03</td>\n",
       "      <td>9.078578e-03</td>\n",
       "      <td>0.002605</td>\n",
       "      <td>0.022523</td>\n",
       "      <td>0.000320</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     aa_000    ab_000        ac_000        ad_000  ae_000    af_000  ag_000  ag_001  ag_002    ag_003    ag_004    ag_005    ag_006    ag_007    ag_008  ag_009    ah_000  ai_000    aj_000  ak_000    al_000     am_0    an_000    ao_000    ap_000    aq_000  ar_000  as_000  at_000  au_000    av_000    ax_000  ay_000  ay_001  ay_002  ay_003    ay_004    ay_005    ay_006    ay_007    ay_008  ay_009    az_000    az_001        az_002    az_003        az_004    az_005        az_006        az_007  az_008  az_009    ba_000    ba_001    ba_002    ba_003    ba_004    ba_005    ba_006    ba_007    ba_008    ba_009    bb_000    bc_000    bd_000    be_000    bf_000    bg_000    bh_000    bi_000    bj_000    bk_000    bl_000    bm_000    bn_000    bo_000    bp_000    bq_000    br_000    bs_000    bt_000    bu_000    bv_000    bx_000    by_000    bz_000    ca_000    cb_000    cc_000  cd_000    ce_000        cf_000    cg_000    ch_000    ci_000  cj_000    ck_000    cl_000    cm_000  cn_000    cn_001  \\\n",
       "0  0.027925  0.003496  9.999998e-01  3.261769e-08     0.0  0.000000     0.0     0.0     0.0  0.000000  0.000163  0.007996  0.038972  0.015907  0.001463     0.0  0.034368     0.0  0.000000     0.0  0.000000  0.00000  0.035022  0.029911  0.022660  0.044285     0.0     0.0     0.0     0.0  0.001274  0.002297     0.0     0.0     0.0     0.0  0.000000  0.003754  0.033205  0.001436  0.007229     0.0  0.000531  0.000465  2.893584e-04  0.000271  5.000101e-03  0.011813  3.681733e-05  1.021497e-07     0.0     0.0  0.010000  0.008791  0.007444  0.007777  0.012332  0.035479  0.058892  0.000250  0.000000  0.000000  0.034739  0.000000  0.000033  0.000133  0.000979  0.034368  0.030469  0.021086  0.017480  0.252354  0.269627  0.228244  0.232853  0.216434  0.420683  0.444702  0.461499  0.172130  0.027925  0.034739  0.034739  0.035415  0.043479  0.001693  0.446972  0.527780  0.041502     0.0  0.050171  2.329835e-10  0.004486  0.000000  0.037208     0.0  0.016536  0.000046  0.026223     0.0  0.000000   \n",
       "1  0.012036  0.003496  0.000000e+00  2.220573e-05     0.0  0.000000     0.0     0.0     0.0  0.000000  0.000080  0.003646  0.018302  0.008157  0.001787     0.0  0.018766     0.0  0.000012     0.0  0.000000  0.00000  0.018180  0.017407  0.013917  0.013244     0.0     0.0     0.0     0.0  0.000000  0.000000     0.0     0.0     0.0     0.0  0.000000  0.000572  0.006052  0.004078  0.000952     0.0  0.000725  0.001724  9.689357e-04  0.000287  8.208840e-03  0.004005  2.279950e-04  1.532245e-07     0.0     0.0  0.005920  0.003845  0.003575  0.004178  0.005457  0.007219  0.008733  0.016044  0.002785  0.000108  0.018907  0.000217  0.001481  0.000449  0.006856  0.018766  0.015318  0.015317  0.008575  0.260487  0.274495  0.279667  0.353789  0.391507  0.420683  0.444702  0.461499  0.006459  0.012036  0.018907  0.018907  0.019221  0.017698  0.006416  0.955934  0.005705  0.019802     0.0  0.000000  2.215927e-05  0.004277  0.000222  0.016250     0.0  0.011610  0.000000  0.000000     0.0  0.000000   \n",
       "2  0.014942  0.003496  1.070067e-07  1.164918e-08     0.0  0.000000     0.0     0.0     0.0  0.000000  0.000007  0.002068  0.020031  0.004624  0.000679     0.0  0.016622     0.0  0.000000     0.0  0.000000  0.00000  0.016839  0.017787  0.003860  0.006013     0.0     0.0     0.0     0.0  0.000451  0.000943     0.0     0.0     0.0     0.0  0.000000  0.000000  0.006817  0.000490  0.013870     0.0  0.000160  0.000255  8.637144e-05  0.000751  1.472287e-02  0.001519  5.264043e-07  0.000000e+00     0.0     0.0  0.003395  0.005779  0.005955  0.006902  0.007536  0.007068  0.005451  0.005705  0.000001  0.000000  0.013861  0.000322  0.000659  0.000711  0.000078  0.016622  0.009000  0.003564  0.003055  0.104646  0.099672  0.304878  0.353789  0.391507  0.420683  0.444702  0.461499  0.026995  0.014942  0.013861  0.013861  0.014372  0.015408  0.000184  0.185489  0.205238  0.017230     0.0  0.012903  0.000000e+00  0.005794  0.000000  0.016475     0.0  0.004260  0.000000  0.000000     0.0  0.000000   \n",
       "3  0.000004  0.000000  3.285295e-08  7.688457e-09     0.0  0.000498     0.0     0.0     0.0  0.000005  0.000010  0.000018  0.000020  0.000000  0.000000     0.0  0.000036     0.0  0.000000     0.0  0.000018  0.00007  0.000072  0.000062  0.000138  0.000040     0.0     0.0     0.0     0.0  0.000076  0.000051     0.0     0.0     0.0     0.0  0.000000  0.000000  0.000000  0.000004  0.000054     0.0  0.000006  0.000001  4.220103e-07  0.000020  6.176496e-07  0.000005  3.712698e-05  4.320932e-05     0.0     0.0  0.000027  0.000003  0.000005  0.000003  0.000003  0.000021  0.000011  0.000001  0.000000  0.000000  0.000112  0.000005  0.000039  0.000000  0.000000  0.000036  0.000057  0.000170  0.000068  0.213954  0.245177  0.304878  0.353789  0.391507  0.420683  0.444702  0.461499  0.010200  0.000005  0.000112  0.000112  0.000116  0.000032  0.000001  0.016485  0.017693  0.000052     0.0  0.000062  2.329835e-10  0.000280  0.000000  0.000015     0.0  0.000082  0.000015  0.000218     0.0  0.000004   \n",
       "4  0.022164  0.003496  6.420405e-07  5.335323e-08     0.0  0.000000     0.0     0.0     0.0  0.000000  0.000191  0.010975  0.019148  0.002078  0.000259     0.0  0.026587     0.0  0.000040     0.0  0.000000  0.00000  0.022935  0.021431  0.013577  0.021556     0.0     0.0     0.0     0.0  0.002251  0.005504     0.0     0.0     0.0     0.0  0.001052  0.002979  0.016674  0.001674  0.005586     0.0  0.000162  0.000080  3.952830e-05  0.000018  2.453857e-04  0.008361  2.486486e-05  0.000000e+00     0.0     0.0  0.005791  0.008906  0.006070  0.006405  0.007245  0.007902  0.008593  0.032891  0.000617  0.000000  0.022239  0.001129  0.001814  0.000792  0.000039  0.026587  0.027012  0.014547  0.008733  0.234058  0.215579  0.209186  0.353789  0.391507  0.420683  0.444702  0.461499  0.182214  0.022164  0.022239  0.022239  0.022984  0.024743  0.000421  0.511293  0.541289  0.026558     0.0  0.027652  0.000000e+00  0.007103  0.000000  0.025291     0.0  0.006840  0.000000  0.010168     0.0  0.000000   \n",
       "\n",
       "         cn_002    cn_003    cn_004    cn_005    cn_006    cn_007    cn_008        cn_009        co_000    cp_000    cq_000    cr_000    cs_000    cs_001        cs_002    cs_003    cs_004    cs_005    cs_006    cs_007    cs_008  cs_009    ct_000    cu_000    cv_000    cx_000    cy_000        cz_000    da_000    db_000    dc_000    dd_000    de_000  df_000  dg_000  dh_000  di_000  dj_000  dk_000  dl_000  dm_000    dn_000    do_000    dp_000        dq_000    dr_000    ds_000    dt_000    du_000    dv_000    dx_000    dy_000  dz_000  ea_000    eb_000     ec_00    ed_000    ee_000    ee_001    ee_002    ee_003        ee_004        ee_005        ee_006    ee_007    ee_008    ee_009    ef_000    eg_000  class  \n",
       "0  0.000000e+00  0.001244  0.007709  0.027562  0.019164  0.002982  0.001486  4.417780e-05  2.562819e-08  0.000484  0.034739  0.000645  0.012483  0.002794  5.815179e-03  0.012301  0.005728  0.010592  0.012140  0.002044  0.000074     0.0  0.000584  0.001000  0.050517  0.001163  0.000000  2.780107e-02  0.000000  0.001868  0.044143  0.010630  0.006391     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0  0.021296  0.045829  0.094192  0.000000e+00  0.000000  0.040779  0.057779  0.032041  0.014773  0.000000  0.000000     0.0     0.0  0.002118  0.023069  0.032751  0.012881  0.017378  0.015918  0.013067  7.421784e-03  8.179508e-03  1.073013e-02  0.001321  0.003800  0.000000  0.000000  0.000000      0  \n",
       "1  6.494771e-07  0.001039  0.006944  0.010922  0.004667  0.001095  0.000688  1.538530e-06  2.219349e-05  0.000000  0.018907  0.000645  0.007340  0.001814  3.577230e-03  0.008252  0.003646  0.004847  0.004085  0.000710  0.000014     0.0  0.000823  0.001667  0.023635  0.007970  0.000294  1.011367e-03  0.000352  0.001392  0.018224  0.007440  0.002963     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0  0.011535  0.019709  0.017052  0.000000e+00  0.000000  0.020787  0.024761  0.009800  0.006837  0.000000  0.000000     0.0     0.0  0.002630  0.020862  0.028186  0.008862  0.008391  0.005407  0.004716  3.019031e-03  4.272917e-03  4.228511e-03  0.000679  0.005064  0.000394  0.000000  0.000000      0  \n",
       "2  0.000000e+00  0.000350  0.007154  0.009360  0.002726  0.000310  0.000321  7.692651e-07  0.000000e+00  0.000012  0.013861  0.000645  0.004271  0.001139  1.222976e-03  0.003529  0.001340  0.004602  0.006622  0.001295  0.000155     0.0  0.000253  0.000398  0.026719  0.000662  0.000024  1.062092e-03  0.000000  0.000000  0.019386  0.003356  0.000863     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0  0.004745  0.020369  0.023377  0.000000e+00  0.000000  0.013231  0.016047  0.000652  0.000378  0.000000  0.000000     0.0     0.0  0.000787  0.009608  0.012318  0.003494  0.004616  0.003559  0.004232  4.364196e-03  7.130884e-03  1.014768e-02  0.001321  0.004937  0.000135  0.000000  0.000000      0  \n",
       "3  4.348078e-05  0.000020  0.000013  0.000007  0.000002  0.000000  0.000000  0.000000e+00  2.329835e-10  0.000004  0.000112  0.000000  0.001230  0.000014  5.207662e-07  0.000015  0.000009  0.000013  0.000005  0.000000  0.000000     0.0  0.000152  0.000011  0.000020  0.000002  0.000000  6.264183e-07  0.000000  0.000000  0.000021  0.000171  0.000352     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0  0.000079  0.000000  0.000000  3.170718e-07  0.000007  0.000010  0.000027  0.000034  0.000014  0.000177  0.000012     0.0     0.0  0.000000  0.000010  0.000652  0.000076  0.000016  0.000003  0.000001  5.970003e-07  7.660803e-07  3.163775e-07  0.000000  0.000000  0.000000  0.008299  0.027923      0  \n",
       "4  6.084575e-06  0.003989  0.014700  0.008428  0.000891  0.000316  0.000368  2.362743e-06  2.353134e-08  0.000427  0.022239  0.000645  0.004697  0.001185  1.756501e-03  0.005359  0.002488  0.006035  0.015422  0.001725  0.000129     0.0  0.001885  0.002268  0.042155  0.004893  0.000000  2.224829e-04  0.000000  0.000000  0.029729  0.004551  0.002520     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0  0.015368  0.033420  0.033052  0.000000e+00  0.000000  0.030069  0.053553  0.000993  0.000634  0.000860  0.007273     0.0     0.0  0.016010  0.010527  0.014202  0.005398  0.009206  0.007981  0.006086  4.171776e-03  6.044861e-03  9.078578e-03  0.002605  0.022523  0.000320  0.000000  0.000000      0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "      <td>0.000022</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.000992</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>0.101243</td>\n",
       "      <td>0.102421</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000122</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000106</td>\n",
       "      <td>0.000046</td>\n",
       "      <td>0.000409</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.378075e-07</td>\n",
       "      <td>9.420836e-05</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>5.271890e-07</td>\n",
       "      <td>1.206865e-07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.319341e-10</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001847</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>7.811493e-07</td>\n",
       "      <td>6.128916e-07</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000178</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000055</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000636</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000116</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.731773e-07</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004391</td>\n",
       "      <td>0.001087</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>7.359084e-07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.191429e-08</td>\n",
       "      <td>4.659671e-09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.268794e-06</td>\n",
       "      <td>0.000070</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.000703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>1.718865e-04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>0.000006</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000071</td>\n",
       "      <td>0.000112</td>\n",
       "      <td>0.000457</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.213954</td>\n",
       "      <td>0.245177</td>\n",
       "      <td>0.304878</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.022483</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>0.000258</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.037088</td>\n",
       "      <td>0.038428</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000148</td>\n",
       "      <td>2.329835e-10</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000572</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.836601e-08</td>\n",
       "      <td>0.000074</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>1.728625e-05</td>\n",
       "      <td>3.620594e-07</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.630885e-09</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002624</td>\n",
       "      <td>0.000064</td>\n",
       "      <td>2.473639e-06</td>\n",
       "      <td>8.250464e-06</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000130</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000088</td>\n",
       "      <td>0.000281</td>\n",
       "      <td>0.000096</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000066</td>\n",
       "      <td>0.000175</td>\n",
       "      <td>0.000227</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.291058e-07</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>0.000094</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.001232</td>\n",
       "      <td>0.000134</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>3.863519e-06</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.024031</td>\n",
       "      <td>0.009804</td>\n",
       "      <td>9.949750e-08</td>\n",
       "      <td>1.304708e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003146</td>\n",
       "      <td>5.936864e-03</td>\n",
       "      <td>0.010896</td>\n",
       "      <td>0.004815</td>\n",
       "      <td>0.000397</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025478</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002241</td>\n",
       "      <td>0.001977</td>\n",
       "      <td>0.025599</td>\n",
       "      <td>0.026936</td>\n",
       "      <td>0.012315</td>\n",
       "      <td>0.011209</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.002915</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000194</td>\n",
       "      <td>0.005336</td>\n",
       "      <td>0.005735</td>\n",
       "      <td>0.004540</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.002270</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.000082</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.000831</td>\n",
       "      <td>5.302458e-02</td>\n",
       "      <td>0.003162</td>\n",
       "      <td>0.011941</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.007139</td>\n",
       "      <td>0.005744</td>\n",
       "      <td>0.006952</td>\n",
       "      <td>0.006122</td>\n",
       "      <td>0.006422</td>\n",
       "      <td>0.007720</td>\n",
       "      <td>0.008154</td>\n",
       "      <td>0.015427</td>\n",
       "      <td>0.004725</td>\n",
       "      <td>0.004825</td>\n",
       "      <td>0.024080</td>\n",
       "      <td>0.002413</td>\n",
       "      <td>0.025609</td>\n",
       "      <td>0.004471</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025478</td>\n",
       "      <td>0.014705</td>\n",
       "      <td>0.015417</td>\n",
       "      <td>0.005805</td>\n",
       "      <td>0.256535</td>\n",
       "      <td>0.148287</td>\n",
       "      <td>0.187106</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.169180</td>\n",
       "      <td>0.024031</td>\n",
       "      <td>0.024080</td>\n",
       "      <td>0.024080</td>\n",
       "      <td>0.024730</td>\n",
       "      <td>0.022661</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>0.789626</td>\n",
       "      <td>0.831950</td>\n",
       "      <td>0.026858</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.025735</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.004860</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.025498</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.006759</td>\n",
       "      <td>0.001134</td>\n",
       "      <td>0.009813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.551300e-04</td>\n",
       "      <td>2.990261e-03</td>\n",
       "      <td>0.006552</td>\n",
       "      <td>0.005902</td>\n",
       "      <td>0.006739</td>\n",
       "      <td>7.515690e-03</td>\n",
       "      <td>1.043624e-02</td>\n",
       "      <td>0.039886</td>\n",
       "      <td>0.005536</td>\n",
       "      <td>6.057572e-09</td>\n",
       "      <td>0.000185</td>\n",
       "      <td>0.024080</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.029572</td>\n",
       "      <td>0.002197</td>\n",
       "      <td>3.529493e-03</td>\n",
       "      <td>5.068237e-03</td>\n",
       "      <td>0.002911</td>\n",
       "      <td>0.008014</td>\n",
       "      <td>0.004376</td>\n",
       "      <td>0.000472</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000248</td>\n",
       "      <td>0.000780</td>\n",
       "      <td>0.044035</td>\n",
       "      <td>0.043329</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.482523e-05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.029926</td>\n",
       "      <td>0.009476</td>\n",
       "      <td>0.003928</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.008643</td>\n",
       "      <td>0.005035</td>\n",
       "      <td>0.007193</td>\n",
       "      <td>1.615699e-03</td>\n",
       "      <td>0.025503</td>\n",
       "      <td>0.022068</td>\n",
       "      <td>0.029054</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.038802</td>\n",
       "      <td>0.018692</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.019663</td>\n",
       "      <td>0.019410</td>\n",
       "      <td>0.026061</td>\n",
       "      <td>0.005285</td>\n",
       "      <td>0.005479</td>\n",
       "      <td>0.006353</td>\n",
       "      <td>0.010074</td>\n",
       "      <td>0.004530</td>\n",
       "      <td>0.004693</td>\n",
       "      <td>0.041604</td>\n",
       "      <td>1.285164e-03</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.021778</td>\n",
       "      <td>0.003496</td>\n",
       "      <td>4.740211e-07</td>\n",
       "      <td>1.090363e-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.415448e-04</td>\n",
       "      <td>0.005493</td>\n",
       "      <td>0.017869</td>\n",
       "      <td>0.017921</td>\n",
       "      <td>0.005231</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>0.023877</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>0.025179</td>\n",
       "      <td>0.024985</td>\n",
       "      <td>0.008374</td>\n",
       "      <td>0.016562</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000699</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002042</td>\n",
       "      <td>0.003703</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>0.008546</td>\n",
       "      <td>0.005985</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000348</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.004897</td>\n",
       "      <td>0.021645</td>\n",
       "      <td>0.002432</td>\n",
       "      <td>1.610178e-06</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005513</td>\n",
       "      <td>0.007982</td>\n",
       "      <td>0.006184</td>\n",
       "      <td>0.007201</td>\n",
       "      <td>0.007742</td>\n",
       "      <td>0.008239</td>\n",
       "      <td>0.011577</td>\n",
       "      <td>0.043332</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.021783</td>\n",
       "      <td>0.000247</td>\n",
       "      <td>0.000777</td>\n",
       "      <td>0.001086</td>\n",
       "      <td>0.000313</td>\n",
       "      <td>0.023877</td>\n",
       "      <td>0.016081</td>\n",
       "      <td>0.007382</td>\n",
       "      <td>0.006912</td>\n",
       "      <td>0.134279</td>\n",
       "      <td>0.159014</td>\n",
       "      <td>0.121599</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.096525</td>\n",
       "      <td>0.021779</td>\n",
       "      <td>0.021783</td>\n",
       "      <td>0.021783</td>\n",
       "      <td>0.022553</td>\n",
       "      <td>0.029907</td>\n",
       "      <td>0.000647</td>\n",
       "      <td>0.429032</td>\n",
       "      <td>0.465209</td>\n",
       "      <td>0.027118</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.023366</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.006729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.024029</td>\n",
       "      <td>0.000634</td>\n",
       "      <td>0.010818</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.445452e-04</td>\n",
       "      <td>0.005005</td>\n",
       "      <td>0.006533</td>\n",
       "      <td>0.012970</td>\n",
       "      <td>1.161361e-02</td>\n",
       "      <td>1.778375e-03</td>\n",
       "      <td>0.000825</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>1.488765e-07</td>\n",
       "      <td>0.002603</td>\n",
       "      <td>0.021783</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.008157</td>\n",
       "      <td>0.001846</td>\n",
       "      <td>1.520854e-03</td>\n",
       "      <td>8.153439e-03</td>\n",
       "      <td>0.002555</td>\n",
       "      <td>0.006474</td>\n",
       "      <td>0.012569</td>\n",
       "      <td>0.002605</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001665</td>\n",
       "      <td>0.001905</td>\n",
       "      <td>0.025123</td>\n",
       "      <td>0.001453</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.518383e-05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.004774</td>\n",
       "      <td>0.028271</td>\n",
       "      <td>0.006569</td>\n",
       "      <td>0.002350</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.811514e-07</td>\n",
       "      <td>0.001684</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.009485</td>\n",
       "      <td>0.017793</td>\n",
       "      <td>0.018183</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.026864</td>\n",
       "      <td>0.032433</td>\n",
       "      <td>0.005907</td>\n",
       "      <td>0.003427</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000892</td>\n",
       "      <td>0.014538</td>\n",
       "      <td>0.020264</td>\n",
       "      <td>0.008796</td>\n",
       "      <td>0.007041</td>\n",
       "      <td>0.006939</td>\n",
       "      <td>0.006443</td>\n",
       "      <td>0.004975</td>\n",
       "      <td>0.008450</td>\n",
       "      <td>0.013648</td>\n",
       "      <td>1.756764e-03</td>\n",
       "      <td>0.014619</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000660</td>\n",
       "      <td>0.003496</td>\n",
       "      <td>7.321514e-08</td>\n",
       "      <td>1.630885e-08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.146433e-07</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000881</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000660</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000690</td>\n",
       "      <td>0.000736</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>0.000199</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>0.000429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>0.000576</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000145</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.000088</td>\n",
       "      <td>0.000199</td>\n",
       "      <td>3.096496e-08</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000230</td>\n",
       "      <td>0.000298</td>\n",
       "      <td>0.000176</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>0.001216</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000660</td>\n",
       "      <td>0.000344</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>0.213954</td>\n",
       "      <td>0.245177</td>\n",
       "      <td>0.304878</td>\n",
       "      <td>0.353789</td>\n",
       "      <td>0.391507</td>\n",
       "      <td>0.420683</td>\n",
       "      <td>0.444702</td>\n",
       "      <td>0.461499</td>\n",
       "      <td>0.012244</td>\n",
       "      <td>0.000660</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>0.000607</td>\n",
       "      <td>0.000363</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>0.089900</td>\n",
       "      <td>0.090846</td>\n",
       "      <td>0.000699</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000373</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000374</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000669</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.000456</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>2.669241e-05</td>\n",
       "      <td>6.939472e-06</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.329835e-10</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>1.866079e-06</td>\n",
       "      <td>1.304045e-04</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.000860</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.000058</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000253</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>0.001150</td>\n",
       "      <td>0.001299</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>2.088061e-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>0.000175</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>0.000408</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000367</td>\n",
       "      <td>0.000524</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000615</td>\n",
       "      <td>0.001074</td>\n",
       "      <td>0.000628</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>0.000110</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>0.000867</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>4.030771e-06</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     aa_000    ab_000        ac_000        ad_000  ae_000  af_000  ag_000  ag_001  ag_002    ag_003        ag_004    ag_005    ag_006    ag_007    ag_008    ag_009    ah_000  ai_000    aj_000  ak_000    al_000      am_0    an_000    ao_000    ap_000    aq_000  ar_000  as_000    at_000  au_000    av_000    ax_000  ay_000  ay_001  ay_002  ay_003  ay_004    ay_005    ay_006    ay_007    ay_008        ay_009    az_000    az_001    az_002    az_003    az_004    az_005        az_006    az_007    az_008  az_009    ba_000    ba_001    ba_002    ba_003    ba_004    ba_005    ba_006    ba_007    ba_008    ba_009    bb_000    bc_000    bd_000    be_000    bf_000    bg_000    bh_000    bi_000    bj_000    bk_000    bl_000    bm_000    bn_000    bo_000    bp_000    bq_000    br_000    bs_000    bt_000    bu_000    bv_000    bx_000    by_000    bz_000    ca_000    cb_000    cc_000  cd_000    ce_000        cf_000    cg_000  ch_000    ci_000    cj_000    ck_000    cl_000    cm_000  cn_000  \\\n",
       "0  0.000022  0.000000  9.386557e-09  1.397901e-09     0.0     0.0     0.0     0.0     0.0  0.000042  2.069654e-05  0.000022  0.000020  0.000000  0.000000  0.000000  0.000054     0.0  0.000000     0.0  0.000044  0.000042  0.000082  0.000078  0.001428  0.000018     0.0     0.0  0.000000     0.0  0.000073  0.000223     0.0     0.0     0.0     0.0     0.0  0.000000  0.000000  0.000000  0.000126  1.062436e-07  0.000193  0.000096  0.000005  0.000004  0.000002  0.000013  1.777389e-05  0.000075  0.000001     0.0  0.000038  0.000022  0.000009  0.000010  0.000008  0.000027  0.000005  0.000005  0.000002  0.000000  0.000645  0.000010  0.000020  0.000005  0.000000  0.000054  0.000099  0.002396  0.000076  0.213954  0.245177  0.304878  0.353789  0.391507  0.420683  0.444702  0.461499  0.106995  0.000022  0.000645  0.000645  0.000992  0.000054  0.000017  0.101243  0.102421  0.000089     0.0  0.000122  0.000000e+00  0.000280     0.0  0.000042  0.000000  0.000106  0.000046  0.000409     0.0   \n",
       "1  0.000030  0.000000  3.191429e-08  4.659671e-09     0.0     0.0     0.0     0.0     0.0  0.000000  3.268794e-06  0.000070  0.000039  0.000000  0.000000  0.000000  0.000071     0.0  0.000011     0.0  0.000000  0.000000  0.000165  0.000149  0.000304  0.000050     0.0     0.0  0.000000     0.0  0.000015  0.000703     0.0     0.0     0.0     0.0     0.0  0.000000  0.000000  0.000001  0.000156  0.000000e+00  0.000028  0.000010  0.000004  0.000028  0.000007  0.000007  1.718865e-04  0.000000  0.000000     0.0  0.000054  0.000015  0.000011  0.000007  0.000007  0.000007  0.000043  0.000022  0.000006  0.000003  0.000243  0.000010  0.000007  0.000047  0.000000  0.000071  0.000112  0.000457  0.000069  0.213954  0.245177  0.304878  0.353789  0.391507  0.420683  0.444702  0.461499  0.022483  0.000030  0.000243  0.000243  0.000258  0.000068  0.000000  0.037088  0.038428  0.000115     0.0  0.000148  2.329835e-10  0.000187     0.0  0.000051  0.000000  0.000140  0.000000  0.000572     0.0   \n",
       "2  0.024031  0.009804  9.949750e-08  1.304708e-08     0.0     0.0     0.0     0.0     0.0  0.003146  5.936864e-03  0.010896  0.004815  0.000397  0.000029  0.000000  0.025478     0.0  0.000000     0.0  0.002241  0.001977  0.025599  0.026936  0.012315  0.011209     0.0     0.0  0.000000     0.0  0.000133  0.002915     0.0     0.0     0.0     0.0     0.0  0.000194  0.005336  0.005735  0.004540  0.000000e+00  0.002270  0.000197  0.000082  0.000029  0.000015  0.000831  5.302458e-02  0.003162  0.011941     0.0  0.007139  0.005744  0.006952  0.006122  0.006422  0.007720  0.008154  0.015427  0.004725  0.004825  0.024080  0.002413  0.025609  0.004471  0.000000  0.025478  0.014705  0.015417  0.005805  0.256535  0.148287  0.187106  0.353789  0.391507  0.420683  0.444702  0.461499  0.169180  0.024031  0.024080  0.024080  0.024730  0.022661  0.000056  0.789626  0.831950  0.026858     0.0  0.025735  0.000000e+00  0.004860     0.0  0.025498  0.000000  0.006759  0.001134  0.009813     0.0   \n",
       "3  0.021778  0.003496  4.740211e-07  1.090363e-07     0.0     0.0     0.0     0.0     0.0  0.000000  5.415448e-04  0.005493  0.017869  0.017921  0.005231  0.000557  0.023877     0.0  0.000000     0.0  0.000032  0.000042  0.025179  0.024985  0.008374  0.016562     0.0     0.0  0.000699     0.0  0.002042  0.003703     0.0     0.0     0.0     0.0     0.0  0.000051  0.008546  0.005985  0.000019  0.000000e+00  0.000348  0.000200  0.000100  0.004897  0.021645  0.002432  1.610178e-06  0.000000  0.000000     0.0  0.005513  0.007982  0.006184  0.007201  0.007742  0.008239  0.011577  0.043332  0.000444  0.000000  0.021783  0.000247  0.000777  0.001086  0.000313  0.023877  0.016081  0.007382  0.006912  0.134279  0.159014  0.121599  0.353789  0.391507  0.420683  0.444702  0.461499  0.096525  0.021779  0.021783  0.021783  0.022553  0.029907  0.000647  0.429032  0.465209  0.027118     0.0  0.023366  0.000000e+00  0.006729     0.0  0.024029  0.000634  0.010818  0.000000  0.000000     0.0   \n",
       "4  0.000660  0.003496  7.321514e-08  1.630885e-08     0.0     0.0     0.0     0.0     0.0  0.000000  3.146433e-07  0.000100  0.000881  0.000049  0.000000  0.000000  0.000660     0.0  0.000000     0.0  0.000000  0.000000  0.000690  0.000736  0.000166  0.000199     0.0     0.0  0.000000     0.0  0.000128  0.000429     0.0     0.0     0.0     0.0     0.0  0.000092  0.000576  0.000007  0.000145  0.000000e+00  0.000012  0.000008  0.000004  0.000001  0.000088  0.000199  3.096496e-08  0.000000  0.000000     0.0  0.000230  0.000298  0.000176  0.000123  0.000030  0.000015  0.000010  0.000010  0.000000  0.000000  0.000571  0.000010  0.000013  0.001216  0.000000  0.000660  0.000344  0.000177  0.000109  0.213954  0.245177  0.304878  0.353789  0.391507  0.420683  0.444702  0.461499  0.012244  0.000660  0.000571  0.000571  0.000607  0.000363  0.000008  0.089900  0.090846  0.000699     0.0  0.000373  0.000000e+00  0.000374     0.0  0.000669  0.000000  0.000172  0.000000  0.000000     0.0   \n",
       "\n",
       "         cn_001        cn_002    cn_003    cn_004    cn_005        cn_006        cn_007    cn_008    cn_009        co_000    cp_000    cq_000    cr_000    cs_000    cs_001        cs_002        cs_003    cs_004    cs_005    cs_006    cs_007    cs_008  cs_009    ct_000    cu_000    cv_000    cx_000    cy_000        cz_000  da_000    db_000    dc_000    dd_000    de_000  df_000  dg_000        dh_000    di_000  dj_000  dk_000  dl_000  dm_000    dn_000    do_000    dp_000        dq_000    dr_000    ds_000    dt_000    du_000    dv_000    dx_000    dy_000  dz_000  ea_000    eb_000     ec_00    ed_000    ee_000    ee_001    ee_002    ee_003    ee_004    ee_005    ee_006        ee_007    ee_008    ee_009  ef_000  eg_000  class  \n",
       "0  1.378075e-07  9.420836e-05  0.000049  0.000008  0.000013  5.271890e-07  1.206865e-07  0.000000  0.000000  9.319341e-10  0.000024  0.000645  0.000000  0.001847  0.000032  7.811493e-07  6.128916e-07  0.000012  0.000001  0.000104  0.000178  0.000130     0.0  0.000024  0.000057  0.000065  0.000029  0.000000  0.000000e+00     0.0  0.000000  0.000055  0.000157  0.000636     0.0     0.0  0.000000e+00  0.000000     0.0     0.0     0.0     0.0  0.000116  0.000000  0.000000  1.731773e-07  0.000011  0.000047  0.000101  0.000002  0.000007  0.000000  0.000001     0.0     0.0  0.000000  0.004391  0.001087  0.000100  0.000032  0.000014  0.000004  0.000004  0.000011  0.000002  7.359084e-07  0.000000  0.000000     0.0     0.0      0  \n",
       "1  0.000000e+00  6.836601e-08  0.000074  0.000036  0.000021  1.728625e-05  3.620594e-07  0.000000  0.000000  1.630885e-09  0.000109  0.000243  0.000000  0.002624  0.000064  2.473639e-06  8.250464e-06  0.000009  0.000005  0.000130  0.000169  0.000050     0.0  0.000088  0.000281  0.000096  0.000033  0.000000  0.000000e+00     0.0  0.000000  0.000066  0.000175  0.000227     0.0     0.0  0.000000e+00  0.000000     0.0     0.0     0.0     0.0  0.000120  0.000000  0.000000  6.291058e-07  0.000012  0.000040  0.000094  0.000082  0.000030  0.000056  0.000009     0.0     0.0  0.000000  0.000027  0.001232  0.000134  0.000034  0.000014  0.000007  0.000017  0.000002  0.000003  3.863519e-06  0.000000  0.000000     0.0     0.0      0  \n",
       "2  3.551300e-04  2.990261e-03  0.006552  0.005902  0.006739  7.515690e-03  1.043624e-02  0.039886  0.005536  6.057572e-09  0.000185  0.024080  0.000000  0.029572  0.002197  3.529493e-03  5.068237e-03  0.002911  0.008014  0.004376  0.000472  0.000009     0.0  0.000248  0.000780  0.044035  0.043329  0.000000  1.482523e-05     0.0  0.000000  0.029926  0.009476  0.003928     0.0     0.0  0.000000e+00  0.000000     0.0     0.0     0.0     0.0  0.008643  0.005035  0.007193  1.615699e-03  0.025503  0.022068  0.029054  0.000021  0.000039  0.038802  0.018692     0.0     0.0  0.019663  0.019410  0.026061  0.005285  0.005479  0.006353  0.010074  0.004530  0.004693  0.041604  1.285164e-03  0.000027  0.000000     0.0     0.0      0  \n",
       "3  0.000000e+00  2.445452e-04  0.005005  0.006533  0.012970  1.161361e-02  1.778375e-03  0.000825  0.000012  1.488765e-07  0.002603  0.021783  0.000645  0.008157  0.001846  1.520854e-03  8.153439e-03  0.002555  0.006474  0.012569  0.002605  0.000177     0.0  0.001665  0.001905  0.025123  0.001453  0.000000  3.518383e-05     0.0  0.004774  0.028271  0.006569  0.002350     0.0     0.0  4.811514e-07  0.001684     0.0     0.0     0.0     0.0  0.009485  0.017793  0.018183  0.000000e+00  0.000000  0.026864  0.032433  0.005907  0.003427  0.000000  0.000000     0.0     0.0  0.000892  0.014538  0.020264  0.008796  0.007041  0.006939  0.006443  0.004975  0.008450  0.013648  1.756764e-03  0.014619  0.000848     0.0     0.0      0  \n",
       "4  0.000000e+00  0.000000e+00  0.000069  0.000456  0.000151  2.669241e-05  6.939472e-06  0.000004  0.000000  2.329835e-10  0.000020  0.000571  0.000645  0.000172  0.000032  1.866079e-06  1.304045e-04  0.000024  0.000081  0.000860  0.000154  0.000058     0.0  0.000253  0.000243  0.001150  0.001299  0.000047  2.088061e-07     0.0  0.000000  0.000790  0.000175  0.000204     0.0     0.0  0.000000e+00  0.000000     0.0     0.0     0.0     0.0  0.000184  0.000192  0.000408  0.000000e+00  0.000000  0.000367  0.000524  0.000005  0.000003  0.000120  0.000029     0.0     0.0  0.000615  0.001074  0.000628  0.000136  0.000101  0.000098  0.000110  0.000190  0.000867  0.000100  4.030771e-06  0.000004  0.000000     0.0     0.0      0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.head()\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ML Predictive models on the original data: No data generation included"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import f1_score, make_scorer\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "from sklearn import svm\n",
    "from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "import xgboost as xgb\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#scoring_fn = \"f1_weighted\"\n",
    "scoring_fn = APS_cost_fn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = df_train['class']\n",
    "y_test = df_test['class']\n",
    "\n",
    "X_train = df_train.drop(['class'], axis=1)\n",
    "X_test = df_test.drop(['class'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "60000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "16000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X_train)\n",
    "len(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# LR_hyperparameters = dict(C=[0.01, 1, 10, 100],\n",
    "#                                max_iter=[6000])  # hyperparameter options\n",
    "\n",
    "# # Best options obtained from running the params mentioned above\n",
    "#LR_hyperparameters = dict(C=[1], max_iter=[6000])  # hyperparameter options => best if PCA is used\n",
    "LR_hyperparameters = dict(C=[10], max_iter=[6000])  # hyperparameter options"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 12 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done   3 out of   5 | elapsed:   16.4s remaining:   10.9s\n",
      "[Parallel(n_jobs=-1)]: Done   5 out of   5 | elapsed:   16.6s finished\n"
     ]
    }
   ],
   "source": [
    "LR_clf = GridSearchCV(LogisticRegression(class_weight=\"balanced\", random_state=RANDOM_STATE),\n",
    "                               param_grid=LR_hyperparameters, cv=5,\n",
    "                               verbose=2, scoring=scoring_fn, n_jobs=-1)\n",
    "\n",
    "LR_best_model = LR_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluating on Testing-set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best estimator:  LogisticRegression(C=10, class_weight='balanced', dual=False,\n",
      "                   fit_intercept=True, intercept_scaling=1, l1_ratio=None,\n",
      "                   max_iter=6000, multi_class='auto', n_jobs=None, penalty='l2',\n",
      "                   random_state=42, solver='lbfgs', tol=0.0001, verbose=0,\n",
      "                   warm_start=False)\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.98      0.99     15625\n",
      "           1       0.48      0.93      0.63       375\n",
      "\n",
      "    accuracy                           0.97     16000\n",
      "   macro avg       0.74      0.95      0.81     16000\n",
      "weighted avg       0.99      0.97      0.98     16000\n",
      "\n",
      "[[15243   382]\n",
      " [   26   349]]\n",
      "Accuracy: 0.9745\n",
      "roc_auc_score: 0.9531093333333334\n",
      "precision_score: 0.4774281805745554\n",
      "recall_score: 0.9306666666666666\n",
      "f1_score: 0.6311030741410488\n",
      "CM: FP 382\n",
      "CM: FN 26\n",
      "APS Cost =  16820\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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13KENI8dhfTqGYRhGtpGvajply5bV6tWrh9sMwzCMXMXKlSv3q2qayzNkhnwlOtWrV2fFiszOTWkYhpG/EZEdwcrLvNcMwzCMbMNExzAMw8g2THQMwzCMbMNExzAMw8g2sl10RKSyiIwRkaUiclxENNBp1UWkgIg8JiLbReSkiKwRkcxOHGgYhmGEiXDUdGrjrI4Xh//lh9PjWZxZkt/AmQH3J+CTNJZWNgzDMHIY4XCZXqKq5QFEpDcBLi7krn/xMPCCqr7sBi8Ukdo4M73OCYWxhmEYRvDI9pqOqiZlMWlHoBDwvk/4+0AjEalxVoYZhmEYKThzOgGNjw9qnrlpcGgDnDVRtviEr3e/6+MswWwYhpF/UIXTp+HYMYiP//dzNv+PHWPvMaXd8Rt4JNWq9mdHbhKdMsAhTT1Z3EGv7akQkbuBuwGqVg1o6XjDMIzgc+ZM8ETB939iYuB2iECxYlC06L+fYsWgeHGoUCH5f2yRopT7vDjjk66DP9cE7TDkJtHJEqo6EWcVR5o3b26zmxqGkTZJSWdVO0g37unTmbOlSJGUouD5XaaMf9EI9H/hwo7w+KCqTJmyhpYtq1CnTgwCfDDoKKVKFaZIkaeCc3zJXaITB5QSEfGp7XhqOAf9pDEMI6+hCidOBL+2EB/v5JsZoqL8P9jLl4datdJ+8GckEkWKQIHs63LfuHEf/frNZvHiHVxxRU3mz78NEeGcc4oHvazcJDrrcdYMqUXKfp367veGbLfIMAz/ePoZgl1bOHYMjh938g+UyEj/D/YyZaBKlazVFjyfyNz0CE3NiRNneO6573jppR84cyaJ2Ngi9OzZJKRl5qYjNg84A/QAnvYKvw1nPXhzIjCMzOLbzxDM2kNm+xn8Pdi9+xmyIgzFikGhQqE7frmYefO20L//HLZujQPg7rvP5/nnr6BMmeiQlhsW0RGR692fF7jfV4vIPmCfqi524yQA76nqXQCquldERgGPichRYBVwE9AO6JqtO2AY2cnZ9DNk9D+z/QzR0f4f7GXKZF0U0ulnMELD338f45prPuTUqUQaNSrH+PFduOSSKtlSdrhqOp/4/B/nfi8G2rq/I9yPN0/gLNP7AFAB+B24UVW/DI2ZhhEg3v0MwRaGs+ln8H6wly9/dsKQzf0MRnBJTEyiQAFBRKhQoRjPPHM5IjBw4MUULOj7qA0d+Wq56ubNm6st4paPyWo/QyD/4+Mz188QERF4x3JmRSKX9zMYwWflyt3cc8+XDBx4Mbfd1jjT6UVkpao2D4YtdnUaOY+EhOALw9n0M/h7sHtqDVkVhkKFrDnJCDlHjpxiyJAFjB27nKQkZfTon+jRoxESxmvPRMfIGr79DMEUiaz0M/h7sHt7JmWlNmH9DEYuRVX59NMNPPDAPPbsOUZEhPDQQy0ZNqxtWAUHTHTyNr79DMFwV81qP0OhQv4f7N41hqz0NVg/g2GkYN++eHr2nMHcuc7Ikosvrsz48Z1p0qRCmC1zMNEJN979DKHoazibfgbPg710aahc+ew6oa2fwTCyhRIloti6NY5SpQrzwgvt6dPnAgoUyDk1dnsSBEoo+hk8/7Paz+D7kC9X7uymx7B+BsPIlSxZsoMGDWKJiSlCVFQkH398A+XLF6V8+WLhNi0VJjoeXn8dvvoqbWHIaj+D74O9cuWzE4boaBMGwzAA2L//OIMGfc3kyavp3bsZb73lDFls3Lh8mC1LGxMdDyNHwqlTUK9exjWGQOZNisg+v3fDMPIXSUnK5MmrGTToaw4ePEFUVARVq5ZEVcPuKJARJjoe4uOhRw8YMybclhiGYaTJ+vV76dt3Nt9//ycAV1xRk3HjOnHuuTFhtiwwTHQ8xMc7tRTDMIwcyp9/HqZZswmcOZNEuXJFefXVjtxyS8McX7vxxkQHHCeB06edZjHDMIwcStWqJbn99sYUKhTBiBHtKV06tJNzhgITHXCmSger6RiGkaP4668jDBw4jwEDLqJNm+oAvPVW1xzlAp1ZTHTAaVoDEx3DMHIECQlJvPHGMp58ciHHjp3mzz8P8/PPvRGRXC04YKLjYKJjGEYOYdmyXfTt+yW//PI3ANdccx6vv35Vruq3SQ8THTDRMQwj7Bw5corHH/+WceOWo+r034wZczVdu9YNt2lBxUQHTHQMwwg7Z84k8tFH6ylQQPi//2vJU0+1oWjRvLfqqYkOmOgYhhEWtm6No1Kl4kRFRRITU4QpU66hcuUSNGqUc2cUOFtsel4w0TEMI1s5dSqB4cOXUL/+WEaO/DE5/Oqrz83TggNW03HwiI6N0zEMI8QsXLiNfv1m8/vvBwDYufNwmC3KXkx0wMbpGIYRcvbujefhh+czdeqvANStG8Obb3bm8strhNmy7MVEB6x5zTCMkLJly0Euuugt4uJOEhUVwZAhrRk06BKiovLfIzjTeywixYAYYLeqngm+SWHARMcwjBBSq1ZpmjatQGRkAcaN60zt2mXCbVLYCNiRQES6iMgq4DDwB9DIDZ8kIreGyL7sIT7eWdmyUN5zTzQMI/uJjz/N4MFfs2mT028jIsyYcTNffXVbvhYcCFB0ROQaYCawHxjsk24b0DP4pmUjNsO0YRhBYtas36lffxwvvfQjAwbMTQ4vUSIqz8wqcDYEWtN5CnhXVTsAo322rQMaBtWq7MZExzCMs2TnzsNcd91HdO36obsEQQWGD7883GblOALt06kHPOL+Vp9tcTh9PLkXEx3DMLJIQkISr7/+M0OHLiQ+/gzFihVi+PDL6d//IiIjbSikL4GKzhGgbBrbqgP7gmJNuIiPtzE6hmFkiR07DvH4499y6lQi3bvX47XXrqJSpRLhNivHEqjofA08JiJzgaNumIpIFHAfMDfNlLmB48etpmMYRsAcOXKK4sULISLUqlWGUaM6Uq1aSTp3rhNu03I8gdb9ngAqAL8Dk3Ca2B4FVgOVgWGhMC7bsOY1wzACQFWZNm0t5547hg8+WJscfu+9F5rgBEhAoqOq24HzgS+BK4FEoDXwE9BCVXcHWqCIVBGRT0XksIgcEZHpIlI1wLRVReQ9EflTRE6IyCYRGS4iZ6cYJjqGYWTApk0HuPLKqfToMZ29e+P5/PPfwm1SriTgwaGq+hdw19kUJiJFgAXAKRw3awWGAwtFpLGqxqeTtijwDVAQeBL4E7gQeBo4F7gpy4aZ6BiGkQYnTybw4ovfM2LE95w+nUhMTDQjR15Jz55Nw21ariQg0RGRBcC9qppK2kWkDjBeVdsFkFUfoCZQV1W3uOl/BTYD9wCj0knbCkdcOqrqfDdsoYiUAR4WkSKqejyQ/UmFiY5hGH7YsuUgnTp9wObNBwG4886mjBx5JWXLmuNRVgm0T6ctkJY7RnGgTYD5dAV+8ggOgKpuA34AumWQ1jNdwBGf8EM4+5H1UVcmOoZh+KFKlRIUKCDUq1eWRYt68u673UxwzpLMOJH7js/xUAs4FmAeDXAGk/qyHqifQdpvcGpEL4pIfREpJiLtgAdwalppNs2li6qJjmEYACQlKW+9tZIDB5xGk6ioSObM6cHq1X1p06Z6eI3LI6TZvCYi/wX+6/5VYKKIHPWJFo0zG8G3AZZXBmcwqS8HgdLpJVTVkyJyKfAZjkh5mITjtu0XEbkbuBugalU//gonTzrCY+N0DCNfs2bN39xzz5f8/PMuli3bxVtvdQWgZs10H01GJkmvppOE46WWiNN05f3f8zkAvMlZOhgEgogUBj4CygG34zTpDcJxIBibVjpVnaiqzVW1eWxsbOoItpaOYeRrjh07zcMPz+eCCyby88+7OOecYnToUCvcZuVZ0qzpqOp7wHsAIrIQ6OfPkSCTxOG/RpNWDcibu3D6lmqr6h9u2BIROYxTCxuvqmsybZEta2AY+ZYZM35jwIC5/PXXEQoUEO6//yKefbYdJUpEhdu0PEtA3muqGqxZ69bj9Ov4Uh/YkEHaRkCcl+B4WOZ+1wNMdAzDCIi1a//h2ms/AqB584qMH9+ZCy6oGGar8j6ZWsRNRJoAdYHCvttUdUoAWXwBvCwiNVV1q5tndRx36EczSPs3UFpEant7vwEt3O9dAZSfGhMdw8g3JCUpBQo4jq6NGpXn/vsv4txzY+jXrzkRETY5Z3YQ6DidUsBs4GJPkPvt7dEWiOi8hdPpP1NEhrjpnwV2AhO8yquGs1DcM6r6jBs8Gfg/YI6IPIczOLQ5zkDRlThu15nHRMcw8gU//riTfv1mM2bM1bRuXQ2A1167OsxW5T8ClfYROMsXtMYRnGuBdsAHwFbgokAycd2a2wGbgKlu+m1AO1X1drsWIMLbPncqnotx5nsbDszBGWw6EbhSVZMC3JeUmOgYRp7m4MET3H33LFq1eodff/2Hl17K2vupERwCbV7riDPdzE/u/79UdSWwSETexBkrc0cgGanqn0D3DOJsx89gT1XdANwYoM2BYaJjGHkSVeX993/loYfms2/fcQoWLMAjj7TiiScuC7dp+ZpAReccYKuqJorISZxZCDxMBz4MumXZhUd0bJyOYeQZ/vzzMD17zmDRou0AtGlTjTff7Ey9en6GTRjZSqDNa38DpdzfO4CWXttqB9Wi7MbG6RhGnqNo0YKsXfsPZcsWYfLkbixc2NMEJ4cQaE3ne5z+lC9x+mKecr3OEnBmi/4iFMZlC9a8Zhh5goULt3HJJVWIiookJqYIM2bcTL16ZYmJsVaMnESgNZ2nga/c3yNxZgDoDNyCIzgDgm9aNmHNa4aRq9mz5yg33/wp7dpNYeTIH5PDL720qglODiTQwaF/4Lgwo6pngIfcT+4nPh6io6GA+egbRm4iMTGJCRNW8thj33LkyCmioyMpWrRguM0yMiBTg0P9ISLNgKGqem0Q7Ml+bIZpw8h1rFq1h759v2T5cmfR4s6dz+WNNzpRvXqpDFIa4SZd0RGRCOACoCrwh6r+4rWtOfAU0AnwnX0692CiYxi5ihUrdtOixSSSkpRKlYrz+utXc+215yGS9SW1jOwjvaUNKgMzgGY4Y2ZURD7FmeF5HM6yByeBV4AXQ29qiDDRMYxcxQUXnEP79jVo2LAcTz/dluLFbXLO3ER6NZ0XgPNwpplZBdQAHseZbuYCnBmoH1XVf0JtZEiJjzcnAsPIwWzffoiHHprP88+3p06dGESEuXN72FxpuZT0RKc9MExVX/YEiMjvOCt4jlHVB0JtXLZw/LjVdAwjB3LmTCKjRi3l6acXc+JEAqrK9Ok3AZjg5GLSE51Y/p32xsNS9/uT0JgTBuLjoXz5cFthGIYX33//J337fsn69fsAuOWWhowa1THMVhnBID3RKQCc9gnz/D8eGnPCgPXpGEaO4cCB4wwe/A1vv+34LNWqVZpx4zrbSp55iIxcpv8jIg29/hfAWY6gq4g09Y6oqu8E27hswUTHMHIMBw+e4P33f6VgwQI8+uilPPbYpURH29ibvERGovNEGuFDff4rYKJjGEam2bo1jho1SiEinHtuDJMmdaV584qcd17ZcJtmhID0RKdGtlkRTkx0DCMsnDhxhuHDlzBy5I+88043brutMUDyt5E3SVN0VHVHdhoSFhIT4dQpEx3DyGbmzdtC//5z2Lo1DoANG/aF2SIjuzjraXByNZ5lDWycjmFkC7t3H+XBB7/i44/XA9CoUTkmTOhCy5ZVwmyZkV3kb9GxZQ0MI9tYvnwX7dtP4ejR0xQpUpCnn27LAw+0oGDBiHCbZmQjJjpgomMY2UDjxuWpWLE4deuWZcyYq6latWS4TTLCQP4e1muiYxgh4/DhkzzyyNccOOA0Y0dFRfLjj3cxc+bNJjj5GKvpgImOYQQRVeWTTzYwcOA89uw5xqFDJ5k48T8AlCkTHWbrjHCTKdERkQJAfSAGWKGq8SGxKrsw0TGMoLJ1axz9+89h3rwtAFx8cWX6978wzFYZOYmAm9dEpD/wN7AGWADUdcNniMj9oTEvxJjoGEZQOH06kREjvqNBg3HMm7eFUqUKM2FCF374oRdNmlQIt3lGDiIg0RGRPsBrOOvr3ISzvo6H74DuwTctGzDRMYygsGLFbp54YgEnTyZw222N+e23/tx99wUUKGALqxkpCbR57f+AV1R1sLuaqDe/AYOCa8jHO1QAACAASURBVFY2YeN0DCPLxMefpmjRQgBcckkVhg5tTZs21WnXLn9MZmJkjUCb12oAX6WxLR7InQuTW03HMDJNUpLy9turqFZtNEuW/DtxydNPX26CY2RIoKKzH6iexra6wK6gWJPdmOgYRqZYt24vbdpMpnfvWRw4cIL//W9tuE0ychmBNq99CQwVkUWA59VGRaQs8CBOX0/uIz4eIiKgUKFwW2IYOZr4+NM8++wSXnllKQkJSZQvX5RXX+3IzTc3zDixYXgRaE1nCHAKWIezXLUCrwMbgUTgmUALFJEqIvKpiBwWkSMiMl1EqmYifT0R+URE9ovICRH5XUSytnS2Z4Zpsc5Ow0iLX37ZQ4MG43jxxR9ITEyiX7/m/PbbfdxySyPE7h0jkwRU01HV/SLSHBgIdAT+cNO+AbyqqkcCyUdEiuC4W58CeuKI13BgoYg0zmjcj2vDAmAR0Bs4DJwLFAuk/FTYsgaGkSFVq5bk2LHTNG1agfHjO9OiReVwm2TkYgIeHKqqR4Fn3U9W6QPUBOqq6hYAEfkV2AzcA4xKK6E7MHUK8K2qXuu1aWGWrTHRMYxUJCQkMXnyam6/vTFRUZHExBRh8eI7qVu3LJGR+XvmLOPsCXSczqu+y1Nnka7ATx7BAVDVbcAPQLcM0rYF6pGOMGUaEx3DSMGyZbu48MK36NNnFiNH/pgc3qBBORMcIygEehXdCawUkXUi8oiIVMpieQ1w+oV8WY8zvU56XOp+FxaRn0TkjIjsFZHXRSRrEzodP25jdAwDOHToJP37z+biiyexevXfVK1akmbNbCYBI/gEKjrlgRuBLTjNaztE5BsRuUNEMlNVKAPE+Qk/CJTOIG1F9/sjYD5wJfASTt/OtEzY8C9W0zHyOarKhx+uo169sYwbt4KIiAI88sglbNhwL5071wm3eUYeJFBHgtPAZ8BnIlIGuBnoAUwGxonI56p6e8isdPAI5PuqOtT9vcidIeEFEamnqht9E4nI3cDdAFWr+jjJxcdDuXKhs9gwcjjz5//BLbd8BjizCowf35lGjcqH2SojL5PpRlpVPaiq41S1FXA5Ts3l1gCTx+G/RpNWDcibA+731z7h893vZv4SqepEVW2uqs1jY2NTbrSajpEPUdXk3x061OL66+vz1lv/4bvv/muCY4ScTIuOiBQVkZ4i8jXOmJ2yOLWgQFiP06/jS31gQwBp0yMpQBv+xUTHyGcsXLiNZs0msHmz8w4nInzyyQ307n2+Tc5pZAuBeq8VEJGrROQD4B/gHSAK6AdUUNUbAyzvC+BiEanplXd1oJW7LT3m4ozv6egTfpX7vSJAG/7FRMfIJ+zdG88dd3xOu3ZTWLPmH1566Ydwm2TkUwIdp7MbiMVxJHgBp19lexbKewu4D5gpIkNwBoc+C+wEJngiiUg1nAGoz6jqMwCqekBEngeeFJEjOINEmwNDgfe83bADQtVEx8jzeCbnHDz4G+LiTlK4cCRDhlzGww9fEm7TjHxKoKLzKTBVVX8+m8JUNV5E2gGvAlNx1uX5Fhioqse8ogoQQeqa2DPAUeBe4GFgDzCSrAxYPXUKkpJMdIw8y++/7+e//53J0qV/AU7/zbhxnahVq0yYLTPyM4F6r90XrAJV9U8yWPTNrUWlamBWpwd0FMEYIGpr6Rh5nAIFhFWr9lChQjFGj+7IjTc2sLnSjLCTpuiISGtglaoec3+ni6ouCaplocaWNTDyIEuW7OCyy6oiIpx7bgyff34Tl1xShZIlC4fbNMMA0q/pLAIuBpa5vzWNeOJu811RNGdjomPkIXbuPMyAAXOZOfN3pk69lttuawzA1VefG2bLDCMl6YnO5fzrxtyOtEUnd2KiY+QBEhKSeP31nxk6dCHx8WcoXrwQp08nhtssw0iTNEVHVRd7/V6ULdZkJyY6Ri7np5/+om/fL1mz5h8Arr++PqNHd6RSpRJhtsww0iYgRwIR2Qpcq6pr/GxrCHyhqjVTp8zBmOgYuZg5czbTpcs0VKF69VKMHduJTp2sKc3I+QTqMl0dZzCoPwoD1YJiTXZiomPkYtq3r0HDhuXo0qUOQ4a0pkiRguE2yTACIjPT4KTVp9McOBQEW7IXEx0jF7Fp0wFuvPETDhxwXP2joiJZufJuRoxob4Jj5CrSc5l+EHjQ/avALBE57RMtGmeyzg9DY14IsXE6Ri7g5MkEXnjhe55//ntOn06kQoVivP761QAULJi7HEYNA9JvXtuKM1sAQE+cuc32+cQ5hePhNin4poUYq+kYOZxvvtnKvffOZvPmgwD06tWUoUPbhNkqwzg70vNemwnMBDyjmJ9xl5bOG3hEx2o6Rg7j77+P8dBD85k2bS0A9eqVZfz4LrRunfu6Tg3Dl0CnwflvqA3JduLjoXBhiLAmCiNnsWnTAaZNW0vhwpEMHdqahx66hEKF7Do18gbp9ekMBSap6m73d3qoqmZ+0s1wYjNMGzmIv/46QuXKzvia1q2r8dprV9GlSx1q1sxoFXfDyF2kV9MZBszDWdZgWAb5eJYoyD2Y6Bg5gGPHTjN06ELGjFnGt9/ekdyEdv/9LcJsmWGEhvT6dAr4+51nMNExwoiqMnPm7wwYMJe//jpCgQLCsmW7rN/GyPMEOjg072GiY4SJHTsOMWDAXGbN2gRA8+YVGT++MxdcUDHMlhlG6Al0Gpw6QClVXeb+j8ZZsbMh8JWqvhE6E0PE8ePmuWZkO199tYXrrvuY48fPUKJEFCNGtKNv3+ZEROS9xgTD8EegNZ03gNU4yxwAPIez7PRa4FURUVUdGwL7Qkd8PMTGhtsKI5/RvHlFihQpyH/+U4dRozpSsWLxcJtkGNlKoK9XTYAfAESkAHAHMFhVLwCGA3eHxrwQYs1rRjZw8OAJhgxZwKlTCQDExBRh3bp+fPjh9SY4Rr4k0JpOSeCA+7sZUBr41P2/CHg4uGZlAyY6RghRVaZO/ZWHHprP/v3HKVw4kiFDnAV4y5cvFmbrDCN8BCo6/wC1ge+BDsAfqrrT3VYMSAiBbaHFRMcIEb/9tp9+/WazaNF2ANq0qUb37vXCa5Rh5BACFZ0vgOfdtXPuBCZ4bWuEM09b7sJExwgyJ06cYcSI73jxxR84cyaJsmWL8PLLV3LHHU08U0kZRr4nUNF5FGfdnI44AjTCa1tXYH6Q7QotiYlw8qSJjhFUZs3axPDh3wHQu3czXnjhCmJizEPSMLwJdO61eKBPGtsuCapF2YEta2AEiZMnEyhc2LmNbrihPgsXXkCPHo259NKqYbbMMHImmRocICJlRKSziNzufpcJlWEhxSM6VtMxskhiYhJjxy6jWrXRbN7s+NiICG++2cUExzDSIWDREZHhwC5gFvCe+71LRHLXnGtga+kYZ8WqVXto2fJt7rtvLnv3xvPBB2vDbZJh5BoCnZFgIPA48DbwPvA3UAG4DXhcRPap6ushszLYmOgYWeDIkVPJk3MmJSmVKhVnzJirueaa88JtmmHkGgJ1JOgLvKaqD3qF/Q4sFpFjwL2AiY6RZ1m8eDu33jqd3buPUqCA8OCDF/P0020pXjwq3KYZRq4iUNGpDsxOY9tsoF9QrMkuTHSMTHLOOcXZv/84F11UifHjO9Os2TnhNskwciWB9ukcwJnc0x8N+He2gtyBiY6RAadPJzJ16hpUFYA6dWL44Yde/PhjLxMcwzgLAhWdz4FnXa+1SAARiRSRW4BngM8CLVBEqojIpyJyWESOiMh0Ecm0u4+IPCoiKiLfZzatiY6RHt99t4Pzz5/AHXfMSOEk0Lx5RZsN2jDOkkCb1x7DmfTzPeAdETkIlAEicKbGeTyQTESkCLAAOAX0xFlxdDiwUEQau+OBAsmnJjAE2Bug/SnxiI6N0zG82L//OIMHf80776wGoHbtMlSqZJNyGkYwCXRw6FERaQ10Bi7DEZyDwGJgrnraIDKmD1ATqKuqWwBE5FdgM3APMCrAfN4EPgDqBroPKbBxOoYXqsp7763h4Yfnc+DACQoViuDRR1vx2GOXJQ/8NAwjOKR7R4lIWRy36NpAHPCZqg4+i/K6Aj95BAdAVbeJyA9ANwIQHRG5FTgfuAWYniUrrHnN8GLy5NX06vUFAO3a1WDcuE7UrVs2zFYZRt4kTdERkbrAEsB7pbNHReR6VZ2ZxfIaAP7SrgduyCixiJQGXgUeUdWDWZ5EMT4eChSAKHN3za+oavIknLfe2ojJk9fQp8/59OjRyCbnNIwQkl6v6HDgJNAWKIozm/QyAm8C80cZnBqTLwdx1ujJiJHAJmByoAWKyN0iskJEVuzbt88J9MwwbQ+XfMncuZu5+OK3OXDAaWaNiopk0aKe3HZbYxMcwwgx6YlOC2Coqi5R1ROquh6n36W6iGT7Os8ichnOiqX9MtGHhKpOVNXmqto81rM8tS1rkC/ZvfsoN974CZ06TWPZsl28/vrPydtMbAwje0ivT6cSzqwD3vwOCFAR2JeF8uLwX6NJqwbkzQScaXj+EpFSblgkEOH+P6GqpwKywkQnX5GYmMS4cct54okFHD16miJFCvLMM225//4W4TbNMPId6YmOAIk+YUnud1YHK6zH6dfxpT6wIYO09dxPXz/b4oAHgdEBWWGik29Yvfpvevf+gpUr9wDQrVtdXn/9aqpWLRlmywwjf5KRP+jTIrLf67+nDeJZd6yOB1XVngGU9wXwsojUVNWtACJSHWiFs1BcelzuJ2w0zlihAcAWP9v9Ex9vY3TyCYcPn2Tlyj1UqVKCMWOupls3m5zTMMJJeqLzJ07NwpcdpK6tBNrH8hZwHzBTRIa46Z4FduK1BLaIVAP+AJ5R1WcAVHWRb2YicgiI9LctXY4ft5pOHkVVWbFiNxdeWAmANm2q8+GH3encuQ7FihUKs3WGYaQpOqpaPdiFqWq8iLTDcXueilNz+hYYqKrHvKIKTg0mNHOOxMdDWRuHkdfYujWO/v3nMG/eFhYvvpPWrasBcNNNaU0baBhGdpPtw61V9U+gewZxtvNvU1568dpmyQjr08lTnDqVwMsv/8jw4d9x8mQCpUoVZu/egGZUMgwjm8mfc3yY6OQZFi/eTt++s/ntN6fr8bbbGvPKKx0oV87Or2HkREx0jFzLu+/+kjx9TZ06Mbz5ZmfatasRZqsMw0iP/Cc6qiY6eYSuXetSuXIJ+vQ5n8GDWxEVlf8uZ8PIbeS/u/T0aUhMNNHJhaxbt5eRI39k4sQuREVFEhNThM2bB9hM0IaRi8h/d6utpZPriI8/zbPPLuGVV5aSkJBEw4axDBrUCsAExzByGZm6Y0WkMdAaiAEmqOrfIlIb+EdVj4bCwKBja+nkKmbP3kT//nPYseMwInDvvc3p0+eCcJtlGEYWCUh0RCQKeB+4DseVWYFZwN/ASzgzP2c0o0DOwNbSyRX89dcRHnhgHtOnbwSgadMKjB/fmRYtKofZMsMwzoZAB18+B1wB3A6UJ+UYmrlAxyDbFTpMdHIFCxduY/r0jRQtWpBRozqwfHkfExzDyAME2rx2CzBEVaeJSITPtm1A9aBaFUpMdHIs//xzjPLliwHOeJutW+Po1asZVarY5JyGkVcItKYTA2xMJ4/cswSniU6O49Chk9x772xq1HiNzZsPAM76Nk891dYExzDyGIGKzjagZRrbLiL1ujs5FxOdHIOq8r//reW8897gzTdXcOZMEt9//2e4zTIMI4QE2rw2BXhcRLYDn7lhKiKX46xjMyz4poUIE50cwebNB+jffw5ff70VgFatqvDmm51p1Kh8mC0zDCOUBCo6LwFNcGaGnuSGfQ8UBj5U1TEhsC002DidsDNt2lp69ZrJqVOJlCkTzUsvXcF//9uMAgVsyWjDyOsEJDqqmgjcLCJjcTzVygEHgHmqujiE9gUfG6cTdpo3rwhAz55NGDnySmJj7VwYRn4hU4NDVfU74LsQ2ZI9WPNatrN3bzzvvPMLgwe3QkSoUyeGLVvup3LlEuE2zTCMbCb/zSESHw9RURDh6/ltBJukJGXSpFUMHvwNhw6dpFKl4tx+exMAExzDyKcEOiNBEhksSa2queMpbjNMZwu//voPfft+ydKlfwHQsWMtLrmkSpitMgwj3ARa03mG1KITA3TAGaMzOYg2hRYTnZBy7Nhpnn56Ea+++hOJiUqFCsV47bWruOGG+oiYo4Bh5HcCdSQY5i/cnZ1gFnA4iDaFFhOdkDJx4kpefnkpInDffRcyfHg7SpYsHG6zDMPIIZxVn46qJorIOOANYHRwTAoxJjpB58yZRAoWdFpX+/e/kGXLdvHww5cke6kZhmF4CHRGgvSIAsoEIZ/s4fhxG6MTJM6cSeTll3+kTp03OHDAcUWPiorkww+vN8ExDMMvgToSVPUTXAhoCLwArAimUSElPh5iYsJtRa7np5/+4p57vuTXX/8B4JNPNtC3b/MwW2UYRk4n0Oa17fj3XhPgD6B/sAwKOfHxUNWfhhqBEBd3gsce+5aJE1eiCjVqlOKNNzrRqdO54TbNMIxcQKCi818/YSeBHcByd8aC3IH16WSZL7/cxF13fcHevfEULFiAQYMu4YknWlOkSMFwm2YYRi4hQ9FxPdRWA7tVdV/oTQoxJjpZpkSJKPbujeeyy6oyfnwX6tePDbdJhmHkMgJxJFCcPptmIbYlezDRCZiTJxOYMeO35P+tW1djyZI7Wbz4ThMcwzCyRIaio6pJwE4gbzypT5ww0QmAr7/+g0aN3uTaaz9iyZIdyeGXXVbNBnkahpFlAnWZngAMFJFCoTQm5CQlOd8mOmny99/HuPXWz+jQ4X22bDlI/fqxREXljhmODMPI+QTqSFAcqAVsFZF5wB5SerOpqj4VSEYiUgV4FbgSx/vtG2Cgqqa7ZKSINAfuBloDVYH9ODNeD1HVbQHthUd0bJxOKhITk5g4cSWPPfYthw+fIjo6kqFD2/B//9eSQoVMdAzDCA5pio6IbAWuVdU1wONem3r5ia5AhqIjIkWABcApoKebbjiwUEQaq2p8OslvBhoArwPrgUrAk8AKEWmqqjszKp9E18nOajqpeOGF7xkyZCEAV19dm7FjO1GjRukwW2UYRl4jvZpOdZzZBlDVYMxcANAHqAnUVdUtACLyK7AZuAcYlU7aF32950TkB2Cbm+/QDEu35rU06du3OZ98soEnn2zNddfVs34bwzBCQrDEJFC6Aj95BAfAbRr7AeiWXkJ/7tqqugPYh1PryRgTHQBUlc8/38iVV07l1KkEAGJiivDLL/fQvbvNBm0YRujISHTSXUMnCzQA1vkJXw/Uz2xmIlIPZ+nsjQElMNFhx45DdO36Iddd9zHffLOVyZNXJ28zsTEMI9Rk5EjwtIjsDyAfVdWeAcQrA8T5CT8IZKoDQUQigfE4NZ2304l3N44DAufGumNL8qHonDmTyKuv/sTTTy/m+PEzlCgRxYgR7ejd+/xwm2YYRj4iI9FpitPpnxHBrhEFwhvAJUBnVfUnZACo6kRgIkDzmjWVffvynegsXbqTu+/+knXr9gJw000NGDWqIxUrFg+zZYZh5DcyEp1rVHVZEMuLw3+NJq0akF9E5AWc2ktPVZ0fcOn5tHlty5aDrFu3l5o1SzNuXCc6dqwdbpMMw8innNUibllgPU6/ji/1gQ2BZCAiTwCDgQGqOjVTpeeTcTqqyrp1e2nUqDwAt93WmJMnE7jttsZER9vknIZhhI/s9l77ArhYRGp6AkSkOtDK3ZYuInI/zrieJ1T1jUyXng9qOhs37qNduylceOFbbN58AHAcBPr0ucAExzCMsJPdovMWzto8M0Wkm4h0BWbizO02wRNJRKqJSIKIDPUKuxlnSex5wAIRudjrE5jnW1ISiEDhwsHboxzCiRNnGDJkAU2ajGfRou0ULx7F9u2Hwm2WYRhGCtJsXgvigFDvPONFpB3ONDhTcabB+RZnGpxjXlEFiCClKF7lhl/lfrxZDLTN0IDERKeWk8dcg7/6agv33juHrVudbrHevZvx4otXUqZMdKbyOXLkCHv37uXMmTOhMNMwjBxEZGQkhQsXJjY2lsLZ+CIuquFwPAsPzWNjdUVEBPz9d7hNCRovvPA9jz32LQANG5Zj/PjOtGqV+ZVRjxw5wj///EOlSpWIjo62MTuGkYdRVRISEjh27Bj79u2jfPnylCxZMs34IrJSVYOyHn12N6+Fl6SkPNefc9119ShdujAvvngFq1bdnSXBAdi7dy+VKlWiSJEiJjiGkccREQoWLEjp0qWpXLkyBw4cyLays9t7LbzkAdFZtWoP7723mtGjr0JEqFMnhp07H6Ro0bNbdeLMmTNER2euOc4wjNxPdHQ0p04FMhwzOOQv0fH06eRCjhw5xdChCxkzZhlJSUrLllW4+eaGAGctOB6shmMY+Y/svu/zl+gkJeW6MTqqymefbeSBB+axe/dRIiKE//u/i+nc+dxwm2YYhpFp8p/o5KKazrZtcdx331zmzNkMwEUXVWLChC40bVohzJYZhmFkDROdHMy0aWuZM2czJUtG8cILV9Cnz/lEROQv3w/DMPIW+esJlgtE5+DBE8m/H374Eh56qCW//XYfffs2N8HJBJMnT0ZEkj+FChWiVq1aPP7445w8edJvmuXLl9O9e3fKly9PVFQU1atX595772XXrl1+4585c4Zx48bRqlUrSpUqRVRUFDVq1KBXr16sWrUqlLuX4xg1ahSNGzcmPw3B8CUuLo7evXtTtmxZihYtyhVXXMHatWsDSrt//3569epFbGws0dHRtGjRgq+++ipVvLZt26a4rj2f0aNHJ8dRVZo1a8ZLL70UtH0LKqqabz4XRESo3n+/5kT27YvXXr1maGzsS7p/f3y2l79hw4ZsLzOUvPvuuwroJ598okuXLtX58+drv379FND77rsvVfwpU6ZoRESEtmnTRv/3v//p4sWLdfz48VqzZk2NjY3VNWvWpIh/7Ngxveyyy7Rw4cI6cOBA/fLLL3XRokU6adIkbdu2rZYqVSq7djXsxMXFaZkyZfSTTz4JtylhIykpSVu1aqWVKlXSadOm6dy5c7V169YaExOjO3fuTDftyZMntVGjRnrOOefoO++8o3PmzNHu3btrZGSkLly4MEXcNm3aaOPGjXXp0qUpPnv27EkRb/r06VqqVCk9cOBAQPZndP8DKzRIz+GwC0F2fi4A1cceS/fgZjdJSUn6zjurNCbmRYVhWqjQszpz5m/ZbkdeFZ3NmzenCL/iiiu0SJEimpiYmBy2ceNGjYqK0u7du6cIV1Xdv3+/1qpVS88991w9ffp0cvhdd92lhQoV0h9//NFv+dOnTw/i3mSekydPZltZL7/8slaoUEETEhKCkl922h4sZsyYoYAuWLAgOezQoUNaunRpHTBgQLppp06dqkAKgUlKStJGjRrphRdemCJumzZttFWrVhnak5CQoBUqVNAXX3wxIPuzU3TyX3tNDmpeW79+L23aTKZXry84cOAE7drVYO3afnTtWjfcpuVZzj//fI4fP87+/f+uTfjaa6+RmJjImDFjKFAg5S0RExPDiBEj2Lx5M9OnTwdgz549vPfee/Tp04eWLVv6Lefaa6/N0JbFixdz5ZVXUrJkSYoWLUqTJk14++1/1yMUEYYNG5Yizfbt2xERJk+enBx25513UrlyZZYuXcoll1xCdHQ0jzzyCJ07d+b881Mv0rdnzx4iIyN59dVXk8O2bdtGjx49iI2NJSoqiqZNm/L5559nuA8AkyZN4sYbbyQiIiJF+FNPPcX5559PiRIlKFu2LO3ateOnn35KEWfRokWICNOnT6dPnz7ExsZSvnz55O0TJ06kSZMmFC5cmLJly3LXXXdx8ODBFHm88cYbtGzZkjJlylCqVCkuvvhiZs+eHZDtweKLL76gYsWKXH755clhJUuW5D//+Q8zZ85MN+1PP/1EdHQ0bdu2TQ4TETp06MDy5cvTbN5Nj4iICG644QYmTZqU6bShJn85EkCOEZ2xY5cxcOBXJCQkUa5cUUaN6sCttzbKWWNlBg6E1aszjhdKmjYFr/bqs2X79u2ULFmSmJiY5LBvv/2W5s2bc8455/hN07lzZwoUKMCCBQu46aabWLhwIQkJCXTt2jXLdsycOZPu3bvTqlUrJkyYQNmyZVm/fj07duzIUn6HDx/m5ptv5uGHH2bEiBFER0ezbds2brnlFjZs2ED9+v/OiTtt2jQAbr31VgB27txJixYtKFeuHK+++iqxsbF89NFHdO/enRkzZqS7nzt27OC3337j2WefTbVt165dPPjgg1SuXJn4+Hjef/99WrduzcqVK2nUqFGKuAMGDODqq69m6tSpyX1ujz76KK+88gr3338/I0eOZNeuXQwZMoR169bx448/Jovc9u3b6d27N9WrVychIYFZs2bRpUsX5s6dy1VX+U7TmJLExESnyScDIiIi0r03169fT8OGDVOFN2jQgClTpnDs2DGKFSuWZt4FC6aeAT4qKgqAdevWUalSpeTwX375hZIlS3L8+HHq1avHAw88wF133ZUqfevWrRkzZgxbt26lZs2aqbaHi/wnOjlknE6jRuVJSlLuuecCnn++PaVL22wAoSAxMZGEhASOHj3K559/zmeffcbo0aNTvJXv3LmTCy64IM08ihYtSmxsLDt37kyOD1CtWrUs2aSqPPDAAzRt2pSFCxcm166uuOKKLOUHcOzYMd5//326deuWHNa4cWNKlCjB1KlTef7555PDp06dSocOHZJrFMOGDUNVWbx4cbIYd+zYkZ07dzJ06NB0RcdTc2nSpEmqbd5v2YmJiVx11VU0aNCASZMm8dprr6WIe9FFF6WIv337dkaOHMlTTz3F0KHJk81Tp04dLr30UmbNmsU111wDwMsvv5y8PSkpifbt27Np0ybefPPNDEWnffv2LF68ON04AAsXLkxRE/Hl4MGDVK9ePVV4mTJlAMfJIC3RnS6t5wAAGddJREFUqVu3LkeOHGHjxo3Uq1cvOXzp0qXJeXto3bo1PXr0oE6dOhw6dIgpU6bQu3dv9uzZw5AhQ1Lk26xZM8A5RyY64SRMNZ1du47w5ZebuOceZ8681q2rsWnTfdSqVSYs9gREEGsY4eK8885L8f/ee+/lvvvuC5M1Dr///js7duzg0UcfTdWcl1UKFixIly5dUoRFR0dz/fXX88EHHzBixAhEhLVr17JmzRoGDx6cHG/evHl06tSJkiVLkpCQkBzesWNHBg0axJEjRyhRooTfcnfv3g1AbGxsqm3ffPMNzz33HL/++muKB2eNGjVSxfVtjvz6669JSkqiR48eKWxq0aIFxYsXZ8mSJcmis3LlSp566imWL1/Ovn37kmsudetm3Ew9YcIEjh49mmG8QPLKKrfeeitPPfUUPXv25O233+acc85h4sSJLFmyBCDFNfLMM8+kSNutWzeuvfZannvuOQYOHJhC2DznxHOOcgomOiEmMTGJsWOXM2TIAo4ePU29erG0bu28IedowckjfP7551SuXJl9+/YxatQoxo0bR4sWLbjjjjuS41SuXJnt27enmUd8fDz79u2jSpUqAMnfO3bsyNLDyDO5YuXKlTOdNi1iY2NT9akA3H777bzzzjssWrSIyy+/nKlTp1K8ePHkBzY4k71OmTKFKVOmpGlvWqLjaQrzNAV5WLVqFZ06daJjx47JD9KIiAh69+7t12Xdt2lz7969ANSu7X9pdc8x3LlzJ+3bt6d+/fqMGTOGqlWrEhkZyZNPPsnGjRv9pvWmdu3aATevpUfp0qWJi4tLFe4R29KlS6eZtlSpUkyfPp2ePXvSuHFjAGrVqsWwYcN48skn02z29XDLLbcwY8YM1q5dm6KP0TOX4okTJ9JKGhZMdELIihW7ueeeL1m1ag8A11xzHtWrl8q28g1o2LBh8oOrXbt2NG7cmEGDBtG9e3eKutdC+/btefvtt9mzZ4/fG3z27NkkJSXRrl07wBkrERERwaxZs+jQoUOmbSpbtixAhh3EUVFRnD59OkVYWrMBp9Xf0KZNG6pWrcr7779PmzZtmDZtGtdff32KyV1jYmK47LLLUtR+vKlYsWKaNnqa4+Li4lLk+dlnnxEZGcn06dNT9FfExcVRqlTqe8DXfk++8+fP9/vA9myfN28ehw8f5uOPP04h4sePH0/TZm+C1bzWoEED5s+fnyp8w4YNVK1aNc2mNQ+XXXYZf/zxB1u2bCExMZE6deowcuRIoqOj02369cb3GHoEz3O95RRMdELA4cMnGTJkAWPHLkcVqlQpwRtvdDKvtDATFRXFyJEj6datG+PGjWPQoEEAPPDAA7z77rsMGDCAjz/+OEVzxsGDB3n88cepXbs21113HeA8hO+8804mTpzIrbfe6teDbcaM/2/v3KOjrq49/vkmBBKiXhFFJDyiIi+vSr1YRa8m8i5yKdYWexEKiNW2sFDqwmppqYp6ra9bFa0oGlpE9CriUlGekvgoePVatCgIrSAKuBSLyiPy3PeP80symUwyAzP5TSY5n7V+azLnd8757bMzc/acc/bZ57lqo4lIunTpQmFhITNnzuTKK6+s1WB06tSJ1atXV0s7VK8sSYwcOZLp06dz8cUXs3nzZkaNGlUtz6BBg1ixYgWnnnrqIUcar5i+/Oijj6oZp927d9dYfH/llVfYtGlTzOm1aPr3709WVhabNm2if//+tearMC6Rhm3dunW88cYbCY0kUzW9NnToUEpKSigrK6OoqAhwZ1S98MILlQ4b8ZDEKae4mIo7d+7kkUceYdSoUZU/jmpjzpw55OXl1XDO2LBhQ0Kyh06qfK8z4fo3MFu1qk5/9FQwadJCgxstO/smmzx5se3Ysafen5ksTWWfjpnZWWedZccff7zt3r27Wv7s7GwrLi62J5980srKymzGjBl28sknW+vWre2dd96pVseOHTvs/PPPt7y8PJs0aZItWLDAysrKrKSkxPr16xd3c+hzzz1nWVlZlc9btmyZTZ8+3aZOnVqZZ+rUqZaVlWW33HKLLV261H73u99Zly5dDLCSkpLKfKNHj7aCgoJan7VmzRoDrKCgwDp27GgHDx6sdv/jjz+2448/3nr16mWzZs2y0tJSmz9/vk2bNs3Gjh1bZzvKy8utRYsWdvfdd1dLX7hwoQF22WWX2dKlS+3BBx+0E044wQoKCqyoqKgy3/Llyw2wJUuW1Kj7hhtusNzcXJs8ebK9+OKLtnTpUispKbERI0ZU7odZvXq1NWvWzAYMGGCLFi2yWbNmWadOnezEE0+0Tp061Sl7Kjlw4ID17t3b2rdvb3PnzrWFCxdaUVGRtWrVyjZt2lQtb3Z2tl1++eXV0q6//np7+umnbfny5fbII49Yly5drFu3btU2d7766qs2ePBgmzlzpi1dutTmzZtnQ4cONcBuv/32GjL94Q9/sJycHNu1K/5mc785tD6NToxOKBXs31+1qXDbtl02ZMgT9u67n9XLs+qDpmR0Fi1aZIDdc8891dJXrFhhw4YNs2OPPdZycnKsY8eOdtVVV9XoNCrYu3evTZ8+3Xr37m1HHnmk5eTkWGFhoY0bN65GBINYLFu2zIqLiy0/P9/y8/Pt9NNPt8cee6zyfnl5uU2cONHatm1rRxxxhA0fPtzefPPNQzY6Zma9evUywG6oZXP0J598YuPGjbN27dpZTk6OtW3b1vr162ezZ8+O247hw4dbcXFxjfT77rvPCgsLLTc313r16mVLliyxoqKihI2OmYsUcfbZZ1vLli0tPz/funXrZuPHj6+2y/+pp56yrl27WosWLaxHjx42d+5cGz16dKhGx8zsyy+/tLFjx1qrVq0sLy/P+vTpY6ti/MgFbPTo0dXSxo4dawUFBZaTk2MFBQU2YcKEGtEE1q9fb4MGDbJ27dpZ8+bNLT8/33r37m1PPPFETHn69etnl1xySUKyh2l0mtZx1ZK9vWULxFmYOxT27NnPXXf9hXnz1rBixThatMjMGctod02PJ1FKS0vp06cPGzdupGPHwzu51pNatmzZQocOHVi8eDF9+/aNmz/e998fV50MKdynU1a2kZ49Z/Cb3yznr3/9jJdf/nvK6vZ4MoXi4mL69u3bcANMNkHuvPNOioqKEjI4YdP0jE4KHAm++GIXY8Y8R3Hxn1i7dhtdurRm2bKfMGxYt/iFPZ5GyP3330/79u1pSjMnDRUzo23btjzwwAPpFiUmTWt6LSvL3j54MKk65s79G+PHv8T27d/SokU2U6acz3XXnZex02oV+Ok1j6fpEub0Wmb3lIdKCnZ/799/kO3bv6V//5N48MGL6NzZb/D0eDyeRPFGJw67du1l5cpP6dvXxS4aOfJ02rTJZ8CAkxtWcM4UYGaNrk0ej6duwp7talprOododF58cR2nnvogF130BOvXu53gkhg4sHOj65xzcnIaXLgMj8dT/5SXl9cIY1SfNK2RTpz4SRV8+uk3TJz4MvPnrwWgZ8+2fPvt/jilMps2bdqwefNmCgoKyMvLa3RG1ePxVGFmldHXt23bVu0Mo/qmaRmdOCOd/fsPcv/9bzJ1aik7d+7liCOaM23ahUyY8F2aNWvcg8KKgI5btmxh3759aZbG4/HUN82aNSM3N5eOHTuSm5sb3nNDe1JDII7RueaahTzwwFsA/OAH3bn33kG0bx87um5j5Kijjqo1mrDH4/Gkgsb98z2aOEZn4sSz6dq1NS+88J/Mmze8SRkcj8fjCYPQjY6kDpKekfS1pG8kPSspodgZknIl3Slpq6RySSskXZDwwyOMjpkxd+7fGDFiXqX3Rpcurfngg/EMGdLlEFvl8Xg8nkQI1ehIagm8AnQDRgOjgFOA5ZISCRXwKPBTYCowBNgKLJLUMyEBAkeC9eu/ZODAxxkx4lnmzl3NggXrK7NkZfkFdI/H46kvwl7T+SlwEtDVzP4OIOk9YD1wFXBPbQUlnQGMAC43s5IgrQx4H7gZqP0g9wBTFjffXMZtt73Gnj0HOOaYPO64ox+DB5+SbLs8Ho/HkwChhsGRtAzINbPzotLLAMysqI6yvwV+CxxtZrsj0m8CrgeOMrM9dT0/t1k723PgKgDGjOnJHXf047jjwj2+2uPxeDKNTI4yfSqwOkb6+0CPBMpuiDQ4EWWbA7EPU49gzwHo1u1YSktHU1LyfW9wPB6PJ2TCnl47BtgeI/2fQM2D0BMvW3G/BpKuBK4M3u5Zu3bC6uLiCQmI2ug5FtiWbiEaCF4XVXhdVOF1UUXKzrxu9Pt0zOxh4GEASW+naoiY6XhdVOF1UYXXRRVeF1VIejtVdYU9vbad2COa2kYxiZaFqhGPx+PxeBooYRud93FrM9H0AD5IoOyJgdt1dNm9gD+20+PxeBo4YRud54FzJJ1UkSCpEDgvuFcXLwA5wI8iyjYDLgUWx/NcC3j4EOVtzHhdVOF1UYXXRRVeF1WkTBdhu0znA+8C5cBvAAOmAUcCp5vZziBfJ+AfwM1mdnNE+SeBgcBkYAPwc9wm0XPN7J3QGuLxeDyewyLUkY6Z7QL6AOuA2cAcnPHoU2FwAgRkx5BvLFAC3AIsADoAg7zB8Xg8nswg1JGOx+PxeJo2GR9lOq0BRBsYh6sLSb0kPSxpraTdkjZJmiPpxDDkrg+S+VxE1XO9JJP0en3IGQbJ6kJSd0lPS9oWfE8+lHR1fcpcXyTZX3SU9Kfg+1EuaZ2kWxKMG9mgkNRe0v1Bn7c7+IwXJlg2S9INkjZK+lbSu5IuSfTZGW100h5AtAGRpC5+jPMqvA/4Hi6s0JnA25I61JvQ9UQKPhcV9ZyEW3v8vD7kDINkdSGpF/Am0AK4AhgM3I2b/s4oktFFcH8pcAEuHNdgYCZwLfBYPYpdX3QGhuO2orx2iGWnATcC03H9xUrgaUmDEyptZhl7AVcDB4DOEWknAvuBX8YpewbOkWFsRFoz4EPg+XS3LWRdHBcjrRNwEOfMkfb2haWLqHoWATOAUuD1dLcrDZ+LLNxWhvnpbkcD0MWAoL8YEJV+e1C+Zbrbd4i6yIr4+4qgbYUJlGsD7AFuikpfBryXyLMzeqSDiyy90oKI1QBmtgF4A/h+AmX3AU9FlN0PPAkMlNQi9eLWK4etCzP7Ikbax8AXQEGK5QyDZD4XAEgagRvt3VAvEoZHMrooBrpTR/T3DCMZXTQPXr+JSv8KZ5wz6kwUMzt4mEUH4nTxeFT648BpiUzJZ7rRSWsA0QZGMrqogaTuuF81a5KUKx0kpQtJrYD/Bq4zs0yPdJGMLv49eM2VtFLSPkmfS7pPUl5KpQyHZHSxFHcEy+8l9ZB0hKQ+uNHTQ+Y8c5sCp+JGOtGb8d8PXuN+vzLd6IQeQLQBk4wuqhFsun0IN9J5NHnRQidZXdyJc+uflUKZ0kUyumgXvD4FLAb6A3fgpmOeSJWAIXLYujCzb3FGOAvXwe7ATSm9CDSlCMLHAF9ZMKcWQcL9ZqMP+Ok5LKYD5wIXmVm8mHiNCknnAz8BzozxxWpqVPwofdzMpgZ/l0rKBm6X1N3MMnEkfMhIysUZ3zY4B4RNwHdxTkj7cRvVPQmQ6UYn2QCinWopC5kXQDQZXVQi6XbcURCjzWxximQLm2R0MQM3uvtU0tFBWjMgO3hfbomFXGooJKOLL4PXJVHpi3EL6N8hs6Zfk9HFONwaV2cz+0eQ9qqkr4GHJT1kZu+mTNKGy3bgaEmK+lGWcL+Z6dNrPoBoFcnoAgBJU4BfARPNbHYKZQubZHTRHfgZ7stVcZ0HnBP8nWm/aJP9jtTF4S5Gp4tkdHEasD3C4FTwv8Fr9yRlyxTex7nPnxyVXrGWE7evyXSjk+4Aog2JZHSBpIm48EJTzGx6PckYFsno4sIY17u4BegLgWdSL269kowuXsYtGg+MSh8UvKbsjJWQSEYXnwGtJEU7GJ0dvG5OkYwNnYU4r9/LotJHAqsDb8C6Sbe/eJK+5vm4EcnfcC6PQ3EdxEfAERH5OuHmXadGlX8S9+v1CqAvrkP5Fjefn/b2haUL3ObQg7hO5pyoq0e62xb25yJGfaVk7j6dZL8jvwvSbwP64TYOlwOz0t22MHUBFOLcpdfhNpZeiAs8/A3O+GaF3Z4U6OOHwfVH3D6dnwfviyLy7AcejSp3e9BP/hI35fjHoP8YktBz093wFCiuIzAv+OfvAJ4japNT8IEx4Mao9DzcHoTPAiW+CRSnu01h6wLnpWW1XKXpblfYn4sYdWWs0UlWF7j9J78MOuu9wMfAzUBOutuVBl30AP4H+ARneNcBdwGt0t2uw9RF3O988H5WVLlsXKSOj3Ej4feAHyb6XB/w0+PxeDyhkelrOh6Px+PJILzR8Xg8Hk9oeKPj8Xg8ntDwRsfj8Xg8oeGNjsfj8XhCwxsdj8fj8YSGNzqeekfSmOA43FhXv0OoZ6OkWfUoavTzIuXcL2mDpBJJ7VP8nMLgGWMi0sZIujxG3gpdFqZShjjyFcfQxSZJDwbHQBxOnddI+kGqZfU0fDI94Kcns/gR8GlUWkJx4dLILFwQ0GZAT+Am4FxJPc2sPEXP2Ar0BiLjeo0Jnhl9FPKCIO/WFD37UJgIvAW0xEXw+BXQAfiPw6jrGuB14NmUSefJCLzR8YTJKos4tTFD2GxmK4O/X5e0A2eIvkeKOkxzcf5Wxs1I5SmvNU56DYk1Ebp4RVIb4ApJbc3sszTJ5Mkw/PSaJ+1IGiDpJUlbJe2WtFrStcG5LXWVayvpT5K2SNoTlH8x6Awr8rSU9Ptgamxv8DpF0uF+9t8KXjsH9Z8g6c+StgUyvCdp5KHIGT29JqkUKALOi5jSKg3uVZtek7RA0jsxdHNCMA02KSLtRElzJH0RyLFK0sWHqQeAiud2jHjGWZKekfSppHJJH0q6TREnjUraiItvdllE+2ZF3D9D0vOStgd1vCF3zpGnEeBHOp4wyQ4ieVdgZnYAOAl3CuP9uBh4vYAbgeNwASZrYzau85qMi4d1PG7apyVURg1fhIuZNQ0X6PEc4Le48z+uPYw2VJwB/5WkfKAMd0bLrwMZRgKzJbU0s4cTkTMGv8CdOZ8NXBWkfVNL3tnAXEk9zCxyqnJE8PoEgKQOuNiCnwOTcKOlS4F5koaZWdxI5DEoBA4AGyPSOgKrcKPBHbijBKbi/sc/DvJcDLyEC7Z5Y5D2RSDnmcBrwF+BnwK7cUdNLJV0rpn932HI6WlIpDvonL8a/4Vbn4gVWLBGEE1cgMlmwBRcBPCsiHsbiQg+COzEnf1T23NHBc+5ICp9Ci54ZZs4chtwayBPLs5grQF24Y5ynhDkKY4qtxTXuWcnKGdhUM+YiLTSWvRTocvC4H0e8DXwX1H5VgEvRbx/FNext47KtwQ37VmXHoqDZw4IdHEkMAxnCO+qo1zF/3IkLgpx64h7G3EnkkaXWRbouHlEWnaQ9ly6P8v+Sv7y02ueMLkYOCviGgeVU0EzJH2MMwb7cGf7HI07Hrg23gImS7pa0mmSFHV/EC4S7l8kNau4cCdf5uCMSDx+HchTDqwI/h5sZluAC3BrPqVRZR7HjdIqDraKJ+dhY86Z4RncVJUAJJ0GnIEbBVUwCDe6+DpKF4uAMyQdlcDjFuHa/w0wH3gVN3qrRNJRwXTmP3ARiPcFcgg4pa7Kgym4IuBp4GCEjMIZ8gsSkNHTwPFGxxMmq83s7Yjrw2Bt5XlgCM7Q9MEZpFuDMrl11HdpUPY6XHj1zZKmRqzXtMFNa+2LuipOe2ydgMyPBfJ8BzjWzE43s7Lg3jHE9iL7LOJ+InImy2ycF1lx8H4UVWH7K2gD/ISaurgzuJ+ILsbjdNEPeAq4CDdVGUkJbjrsPqB/kH98cK+u/yU4fWUHdUbLOQF3iJrvszIcv6bjSTcn49ZwRpnZ4xWJkuK64ZrZ57gObbykrrjDtW7CTSP9EfgS2AAMr6WKjQnIt9XMajsh859A1xjpbSPuJyJnspQBm4CRkspw6znPWHWX7i9xayW/r6WOLQk8Z12FLiS9glubukFSiZl9IikXdzjajWZ2b0WhYOSVCF/hpuEeAP4cK4OZZdoR2Z4ovNHxpJuKxfR9FQmScqh5HG6dmNmHwK8l/Qz41yB5IXAJsNPM1qZA1mjKgB9JOs/M3ohIH4Fb06mxB6kWOWOxB7d2EhczM0mP40YD84ECqk+tgdNFb+B9S8H+ouCZk3AebNfjjGoL3EhlX1T2MTGq2INbj4qsc5ek13BTg+94A9M48UbHk27W4NZdbpV0ANdhTaq7CEj6F9w8/xxgbVDu+zhPssVBtjnAWGCZpLtx3lLNcaOrocAwM9udhOyzgKuBZyVNwW18vQw3rXSVmR1IUM5YfAD8QtKluE2jOwKDVRuzcetPD+FGPaVR96fiphVflTQdN8prhTN8J5lZjegH8TCzVZLmAeMk3WpmWyStBK6VtBXYBlyOM4Kx2ne+pCG46chtZrYRd0rpq8AiSY/ipi+PBc7EOWbU5c3oyQTS7cngr8Z/UeVx1bmW+z1xu9N34zrum4EriPDSCvJtJPBew/2qngG8j/MO+wa3YD8iqu5cnFvuWtyv638G+W4EmsWR24Bb4uQ5Adfhb6Pq6N6REffjykls77W2uIX/HUQcIUyU91qULG8F926rRdb2wExgM85hYyvOe21knDYWB/X2i3GvO85t+t6ItrwcyP05MB239lPNyw/ohpvu203UkchBnU8G5fcEn4nncQ4caf88+yu5yx9X7fF4PJ7Q8J4gHo/H4wkNb3Q8Ho/HExre6Hg8Ho8nNLzR8Xg8Hk9oeKPj8Xg8ntDwRsfj8Xg8oeGNjsfj8XhCwxsdj8fj8YTG/wNRdDbzmMdr5gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Best estimator: \", LR_best_model.best_estimator_)\n",
    "# X = X.values.reshape(-1, 1)\n",
    "LR_predict_test = LR_best_model.predict(X_test)\n",
    "LR_pre_prob_test = LR_best_model.predict_proba(X_test)\n",
    "\n",
    "model_evaluaiton(y_test, LR_predict_test,\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Finding the threshold and then evaluate**\n",
    "- y_predict_prob_1 : classifier probability's output for minority class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 15982/15982 [09:39<00:00, 27.58it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best threshold: 0.3413\n",
      "Min cost: 14330.00\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "LR_y_predict_prob_1 = LR_pre_prob_test[:,1]\n",
    "LR_best_th = find_cut_off(y_test, LR_y_predict_prob_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3412506982351115"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LR_best_th"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.96      0.98     15625\n",
      "           1       0.38      0.95      0.54       375\n",
      "\n",
      "    accuracy                           0.96     16000\n",
      "   macro avg       0.69      0.96      0.76     16000\n",
      "weighted avg       0.98      0.96      0.97     16000\n",
      "\n",
      "[[15042   583]\n",
      " [   17   358]]\n",
      "Accuracy: 0.9625\n",
      "roc_auc_score: 0.9586773333333334\n",
      "precision_score: 0.3804463336875664\n",
      "recall_score: 0.9546666666666667\n",
      "f1_score: 0.5440729483282675\n",
      "CM: FP 583\n",
      "CM: FN 17\n",
      "APS Cost =  14330\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LR_predict_test_th = LR_pre_prob_test[:,1] > LR_best_th\n",
    "\n",
    "model_evaluaiton(y_test, LR_predict_test_th, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Just example to prove the point of how the threshold works**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6587493017648884"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0.659"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1.0-LR_best_th)\n",
    "lr_th = round((1.0-LR_best_th),3)\n",
    "lr_th "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6587493017648884"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.96      0.98     15625\n",
      "           1       0.38      0.95      0.54       375\n",
      "\n",
      "    accuracy                           0.96     16000\n",
      "   macro avg       0.69      0.96      0.76     16000\n",
      "weighted avg       0.98      0.96      0.97     16000\n",
      "\n",
      "[[15040   585]\n",
      " [   17   358]]\n",
      "Accuracy: 0.962375\n",
      "roc_auc_score: 0.9586133333333333\n",
      "precision_score: 0.3796394485683987\n",
      "recall_score: 0.9546666666666667\n",
      "f1_score: 0.5432473444613051\n",
      "CM: FP 585\n",
      "CM: FN 17\n",
      "APS Cost =  14350\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LR_predict_test_th_2 = LR_pre_prob_test[:,1] >= LR_best_th\n",
    "# LR_predict_test_th_2 = LR_pre_prob_test[:,0] < (1.0-LR_best_th)\n",
    "LR_predict_test_th_2 = LR_pre_prob_test[:,0] < lr_th\n",
    "\n",
    "(1.0-LR_best_th)\n",
    "model_evaluaiton(y_test, LR_predict_test_th_2, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluate on Training-set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.97      0.99     59000\n",
      "           1       0.38      0.95      0.54      1000\n",
      "\n",
      "    accuracy                           0.97     60000\n",
      "   macro avg       0.69      0.96      0.76     60000\n",
      "weighted avg       0.99      0.97      0.98     60000\n",
      "\n",
      "[[57439  1561]\n",
      " [   54   946]]\n",
      "Accuracy: 0.9730833333333333\n",
      "roc_auc_score: 0.9597711864406779\n",
      "precision_score: 0.37734343837255685\n",
      "recall_score: 0.946\n",
      "f1_score: 0.5394924436840604\n",
      "CM: FP 1561\n",
      "CM: FN 54\n",
      "APS Cost =  42610\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LR_predict_train = LR_best_model.predict(X_train)\n",
    "LR_pre_prob_train = LR_best_model.predict_proba(X_train)\n",
    "\n",
    "model_evaluaiton(y_train, LR_predict_train, \"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# RF_hyperparameters = {\n",
    "#             'n_estimators': [50, 100, 250],\n",
    "#              'max_features': ['auto', 'sqrt', 'log2'],\n",
    "#             # 'max_depth': [5, 6, 8, None],\n",
    "#             'max_depth': [5, 6, 8],\n",
    "#             'criterion': ['gini', 'entropy']}\n",
    "\n",
    "# ## Best Params based on running the previous range of hyperparameter => when PCA is used\n",
    "# RF_hyperparameters = {\n",
    "#                       'n_estimators': [250],\n",
    "#                        'max_depth': [5],\n",
    "#                       'criterion': ['entropy']}\n",
    "\n",
    "\n",
    "## Best Params based on running the previous range of hyperparameter\n",
    "RF_hyperparameters = {\n",
    "                      'n_estimators': [250],\n",
    "                       'max_depth': [5],\n",
    "                      'criterion': ['gini']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 12 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done   3 out of   5 | elapsed:   33.9s remaining:   22.6s\n",
      "[Parallel(n_jobs=-1)]: Done   5 out of   5 | elapsed:   34.0s finished\n"
     ]
    }
   ],
   "source": [
    "RF_clf = GridSearchCV(RandomForestClassifier(class_weight=\"balanced\", random_state= RANDOM_STATE),\n",
    "                               param_grid=RF_hyperparameters, cv=5,\n",
    "                               verbose=2, scoring=scoring_fn, n_jobs=-1)\n",
    "\n",
    "RF_best_model = RF_clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluating on Testing-set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best estimator:  RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight='balanced',\n",
      "                       criterion='gini', max_depth=5, max_features='auto',\n",
      "                       max_leaf_nodes=None, max_samples=None,\n",
      "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
      "                       min_samples_leaf=1, min_samples_split=2,\n",
      "                       min_weight_fraction_leaf=0.0, n_estimators=250,\n",
      "                       n_jobs=None, oob_score=False, random_state=42, verbose=0,\n",
      "                       warm_start=False)\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.96      0.98     15625\n",
      "           1       0.37      0.97      0.54       375\n",
      "\n",
      "    accuracy                           0.96     16000\n",
      "   macro avg       0.69      0.96      0.76     16000\n",
      "weighted avg       0.98      0.96      0.97     16000\n",
      "\n",
      "[[15014   611]\n",
      " [   12   363]]\n",
      "Accuracy: 0.9610625\n",
      "roc_auc_score: 0.964448\n",
      "precision_score: 0.3726899383983573\n",
      "recall_score: 0.968\n",
      "f1_score: 0.5381764269829503\n",
      "CM: FP 611\n",
      "CM: FN 12\n",
      "APS Cost =  12110\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Best estimator: \", RF_best_model.best_estimator_)\n",
    "# X = X.values.reshape(-1, 1)\n",
    "RF_predict_test = RF_best_model.predict(X_test)\n",
    "RF_pre_prob_test = RF_best_model.predict_proba(X_test)\n",
    "model_evaluaiton(y_test,RF_predict_test, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Finding the threshold and then evaluate**\n",
    "- y_predict_prob_1 : classifier probability's output for minority class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 2690/2690 [01:34<00:00, 28.57it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best threshold: 0.4381\n",
      "Min cost: 10790.00\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "RF_y_predict_prob_1 = RF_pre_prob_test[:,1]\n",
    "RF_best_th = find_cut_off(y_test, RF_y_predict_prob_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.96      0.98     15625\n",
      "           1       0.35      0.98      0.52       375\n",
      "\n",
      "    accuracy                           0.96     16000\n",
      "   macro avg       0.68      0.97      0.75     16000\n",
      "weighted avg       0.98      0.96      0.97     16000\n",
      "\n",
      "[[14946   679]\n",
      " [    8   367]]\n",
      "Accuracy: 0.9570625\n",
      "roc_auc_score: 0.9676053333333334\n",
      "precision_score: 0.3508604206500956\n",
      "recall_score: 0.9786666666666667\n",
      "f1_score: 0.5165376495425755\n",
      "CM: FP 679\n",
      "CM: FN 8\n",
      "APS Cost =  10790\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "RF_predict_test_th = RF_pre_prob_test[:,1] > RF_best_th\n",
    "model_evaluaiton(y_test, RF_predict_test_th, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Just example to prove the point of how the threshold works**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.561949219837919"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0.562"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1.0-RF_best_th)\n",
    "rf_th = round((1.0-RF_best_th),3)\n",
    "rf_th"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.561949219837919"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.96      0.98     15625\n",
      "           1       0.35      0.98      0.52       375\n",
      "\n",
      "    accuracy                           0.96     16000\n",
      "   macro avg       0.67      0.97      0.75     16000\n",
      "weighted avg       0.98      0.96      0.97     16000\n",
      "\n",
      "[[14945   680]\n",
      " [    8   367]]\n",
      "Accuracy: 0.957\n",
      "roc_auc_score: 0.9675733333333334\n",
      "precision_score: 0.35052531041069723\n",
      "recall_score: 0.9786666666666667\n",
      "f1_score: 0.5161744022503516\n",
      "CM: FP 680\n",
      "CM: FN 8\n",
      "APS Cost =  10800\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# RF_predict_test_th_2 = RF_pre_prob_test[:,1] >= RF_best_th\n",
    "# RF_predict_test_th_2 = RF_pre_prob_test[:,0] < (1 - RF_best_th)\n",
    "RF_predict_test_th_2 = RF_pre_prob_test[:,0] < rf_th\n",
    "\n",
    "(1 - RF_best_th)\n",
    "model_evaluaiton(y_test, RF_predict_test_th_2, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluating on Training-set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best estimator:  RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight='balanced',\n",
      "                       criterion='gini', max_depth=5, max_features='auto',\n",
      "                       max_leaf_nodes=None, max_samples=None,\n",
      "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
      "                       min_samples_leaf=1, min_samples_split=2,\n",
      "                       min_weight_fraction_leaf=0.0, n_estimators=250,\n",
      "                       n_jobs=None, oob_score=False, random_state=42, verbose=0,\n",
      "                       warm_start=False)\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.96      1.00      0.98     56636\n",
      "           1       0.97      0.29      0.44      3364\n",
      "\n",
      "    accuracy                           0.96     60000\n",
      "   macro avg       0.96      0.64      0.71     60000\n",
      "weighted avg       0.96      0.96      0.95     60000\n",
      "\n",
      "[[56605    31]\n",
      " [ 2395   969]]\n",
      "Accuracy: 0.9595666666666667\n",
      "roc_auc_score: 0.6437512927538851\n",
      "precision_score: 0.969\n",
      "recall_score: 0.2880499405469679\n",
      "f1_score: 0.4440879926672777\n",
      "CM: FP 31\n",
      "CM: FN 2395\n",
      "APS Cost =  1197810\n"
     ]
    },
    {
     "data": {
      "image/png": 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k+vXh++/toNL69eGNN2zyGTAATp1yOjqlVBp0+vRlWrSYQbt23/DHH5eoU6c4mzd354MPmpA9u/P3kTXppAa1asG8ebBtGzRvDu+9Z/u7vfACHD/udHRKqTQkZ05/Dh8+R+7cWfj44xasWdOFatUKOx3WLVpIkBrt3w/vvgvTptnLcZ07w6uvQunSTkemlEqFVq48SqVKBciXLysA27f/SaFC2ShUKLtH9q+FBOld+fLw2Wd2rM/TT8PUqXZZhw6wZ4/T0SmlUokzZ67QufN8GjSYQv/+P95aXrVqIY8lHE/TpJOaBQbCuHFw+DA8/zzMng2VKsEjj8DWrU5Hp5RySHS04bPPfiU4eCxTpmzF3z8TJUvmcrwyzR2adNKCokXhww9ta52BA2HpUqhRA1q2hHXrnI5OKeVFu3adokGDKXTtuoCzZ6/yn/+UZseOZ3j99QaOV6a5Q5NOWpI/P7z9Nhw7ZjscrF8PdetC48Z2crk08ClHKXX7jh27QI0aE1m9+hgFC2Zj+vQ2LF3annLl8jkdmts06aRFuXLBa6/ZM5+RI+19nsaN4d57YdEiTT5KpVMlS+biqaeq0rNnTfbu7c0TT1RJE2c3sWnSScuyZYMXX7T3fCZMgBMn7CW3u+6Cb77RztZKpXHHj1/k4Ye/5uefw28t++STVkyY0JI8edJm+yxNOulBlizQsyccOABTpsCVK7bYoHJlW3atna2VSlOioqIZNWo9ISHjmD17D6+88sOtIgEfn7R1ZhOXJp30xM8POnaE3bth5kz7fYcOEBwMkybB9etOR6iUSsKGDb9z992f8OKL33Pp0g0efLACs2e3S3OX0RKiSSc9ypQJ2rWzZdULFtgChB497LQKo0fbMyGlVKpy8eJ1+vT5jjp1PuXXX09SsmQu5s9/jLlzH6VEiVxOh+cxmnTSMxF44AFb5fbDD1C2rG2tExRkOx5cvOh0hEopl8jIm8ycuQsfH+GVV+qye3cvWrUKdjosj9M2OBnN6tW23HrJEsidG557zj7ypZ2SS6XSi8OHz1GsWA78/X0BWLz4AMWL56RKlUIOR/ZP2gZH3b569WDxYti0CRo1stMpBAba6RVOnnQ6OqUyhOvXoxg6dCUVK45jxIi1t5Y3a1Yu1SUcT9Okk1HVrAlz5sCOHdC6te14UKqUnVju2DGno1Mq3Vq+/AjVqn3M668v5/r1m/z22wWnQ/IqTToZXeXKMH067NsHTz4JEyfaez/dutmGo0opjzh16jIdOswlLOwL9u2LIDg4Hz/91IGJEx9wOjSv0qSjrLJl4dNPbaLp0cMmouBgm4h27XI6OqXStIMHz1KhwlimTduOv38m3n67Edu29aRRo1JOh+Z1yU46IpJdRAJFxC8lAlIOK1kSxoyBI0egb19bcl25MrRpA5s3Ox2dUmlSmTJ5qF69MPffX5qdO3sxaFD9W8UDGY3bSUdEWorIFuACcAio4lr+qYg8kULxKacULgzvvw/h4TB4MCxfDqGh0KyZrYBTSiXo8uUbvPrqD+zfHwGAiDBv3mN8/317ypbN63B0znIr6YjIg8B84AzwapztjgAdPR+aShXy5YMhQ2xz0XfftWc7990HDRvasT8ZqOReKXd8++0+KlYcz/vvr+XZZxffWp4zp3+66SpwJ9w903kD+NwY0wQYFee1nUBlj0alUp+cOe2U2eHhtqvBwYPQpAnUqWMvwWnyURncb79doE2bmbRq9ZVrCoLCDB3ayOmwUh13k04IMNP1ddy/LucAHVmYUWTNageTHjpkK91On7Yl19Wq2X5vN286HaFSXhUVFc3IkesICRnH3Ll7yZ49M6NGNWXDhqepVauY0+GlOu4mnYtA/gReCwJOeyQalXb4+0P37rB//9+drB97DCpWtJ2uIyOdjlAprzh69DyvvbaMy5cjads2hL17e/P883Xw9dXi4Pi4+678AAwQkdyxlhkR8Qf6AIvj30yle76+0L497Nxp5/DJmhU6d4Zy5ewcP9euOR2hUh538eL1W1MNlCmTl5Ejm7Jw4eN88007ihXL6XB0qZu7SWcgUBjYB3yKvcTWH9gKFAfeTIngVBri4wNt28KWLXb20qJFoVcvKF3azm56+bLTESp1x4wxzJixg3LlxjB9+o5by3v1qkWLFuUdjCztcCvpGGPCgbuAhcD9wE2gPrAeqG2MOeHuAUWkhIh8IyIXROSiiMwRkZJubltSRKaKyDERuSoi+0VkqIhkc/f4KoWJQPPmsGYN/PQThITY8T6BgbbR6IWM1fJDpR/790dw//3TePLJOZw6dZm5c/c6HVKa5NUu0yKSFdgGXAcGYc+YhgJZgarGmAQ/DrsSy6+AH/bM6hhQCxgCLDDGPJrU8bXLtEPWrbMJZ9EiyJUL+vSxUyzkT+g2oVKpx7VrUbz33mqGD1/NjRs3yZcvgBEj7qdjx+ppfhZPd3m9y7SI/CQiFRJ4rbyI/OTm8Z4GSgMPGmPmGWPmA62AQKBHEtveC5QDehhjphpjlhtj3gdGA21dCU2lRvfcAwsX2ktv998Pw4fbM5++feGE2yfJSnndwYNnqVp1Am+++TM3btykU6fq7N3bh86da2SYhONp7t7TaQgkdHcsB9DAzf20AtYbY251kjTGHAHWAK2T2Daz6znuzGPnsT+H/gtI7WrUgFmzbC+3tm3teJ9Spey9n/Bwp6NT6l9KlMiJj48QEpKfFSs68vnnrcmfXz/f3onk1PQldB2uDHDJzX1Uwg4mjWsXUDGJbX8EDgDviUhFVw+4MOB54OPELs2pVCYkBL74wpZbd+oEkyfbarfOne0ypRwSHW345JPNRETYKd39/X357rsn2bq1Jw0aBDkbXDqRYNIRkc4islJEVmITzqSY72M9NgJTgVVuHi8vdjBpXGeBPIltaIy5BtRzxbwL+AtYhi1u6JPIz9FdRDaJyKbTp3U4UapSurQdYHr4sL3PM3MmVKhgx/ts3+50dCqD2bbtJHXrTqZ794X07//jreWlS+chc+ZMDkaWviR2phONrVK7ib10Ffv7mEcEMAHomrJhgohkwXZFKAg8hb2k9wrwKDAuoe2MMZOMMaHGmNACBQqkdJjqdhQrBh99ZC+x9e8P331nOxy0bg0bNjgdnUrnLl26wcsvL6VmzUn88svvFCmSnSZNyjgdVrqVYG9tY8xU7FkMIrIceMYYc6c1gueI/4wmoTOg2Lpi7y2VNcYcci1bKSIXsGdhHxtjtt1hfMpJBQvaIoNXXrHTK4weDbVr2+KDgQOhfn1bkq2Uh8ybt5dnn13M8eMX8fERnnvubt5+O4ycOf2dDi3dcnecTiMPJBywl8UqxbO8IrA7iW2rAOdiJZwYMR+FQ+4wNpVa5Mljp1MID4cRI+yltoYNbdJZskSbiyqP2LHjTx56aCbHj18kNLQoGzZ0Y/ToZppwUliymgOJSDURaSciHeI+3NzFAqCOiJSOtc8gbDn0giS2PQnkEZGycZbXdj3/7mYMKq3IkQNeftlOKDd2rJ1eoVkzqFUL5s6F6GinI1RpTHT03x9YqlQpxHPP3c2YMc1Yv74rNWsWdTCyjMOtwaGunmuLgDoxi1zPtzY2xiR5p801wHMbcJW/B4e+jS27rmqMueRaLxA7Udxbxpi3XMuCgO3Y5DMMOzg0FHgd2A/cbYxJ9K+QDg5N427csM1F333XTq1QqRK89hq0a2d7wCmViLVrf+OZZxYxZkwz6tcPdDqcNMXrg0OB4djpC+pjE85DQBgwHTgM3O3OTlxlzWHYJDHNtf0RICwm4bgIkCl2fK5WPHWw/d6GAt9hB5tOAu5PKuGodCBzZujaFfbsgRkz7LInn7Ql2JMn26SkVBxnz16le/dvuffez9i+/U/ef3+N0yFlaO6e6RzCtpuZDkQCtYwxm12vTQCyGWPcvcTmGD3TSWeio+0EckOH2hlNS5SAfv1sYgoIcDo65TBjDF9+uZ2+fZdy+vQV/Px86NfvXgYOvI+AAD+nw0tTnDjTKQIcNsbcBK5hL4fFmAO08EQwSiWLjw88+CBs3GgLDAID4dlnbZeDESPgr7+cjlA55NixC4SFfUGHDvM4ffoKDRoEsm1bT4YODdOE4zB3k85JIGYunaPAPbFei3tjXynvEoGmTWHVKvj5Z6ha1Z7xBAbCW2/BuaSq8VV6ky2bHzt2/En+/FmZMqU1y5d3JCREx+mlBu4mndX8XUQwDXhDRCaKyDhgBPB9SgSnVLLVrw9Ll8Ivv8B998Ebb9jkM2AAnDrldHQqBS1ffoTr16MAyJcvK/PmPcbevb3p2LE6ouO7Ug13k84Q/k4sI7AdAFoAj2NLnZ/1fGhK3YG774b582HbNju/z3vvQVCQnVLh+HGno1Me9Mcff/HYY98QFvYFI0asvbW8Xr2S5MunzTlTG3cHhx4yxqxyfR1pjOlrjClujMlrjHnCGBORsmEqdZuqVoWvvrIVb48+CuPG2Z5vPXrYnm8qzbp5M5rx4zdSocI4Zs7cRUCAL9my6f2a1C5Zg0PjIyI1RGSuJ4JRKsUEB8Pnn8OBA9CtG0ydCuXLQ4cONiGpNGXLlj+4557J9O79HRcvXqdFi3Ls3t2bF1+8J+mNlaMSTToikklE7haRh0WkRpzXQkXkW2AT0Cglg1TKY4KCYPx4e5bz/PMwe7YdZPrII7B1q9PRKTds2nSCWrU+YePGExQrloPZs9vx7bePExSUO+mNleMSm9qgOPALsA74GtgkIjNFJLOIfOp6LQz4EDunjlJpR9Gi8OGHtrXOa6/Z4oMaNaBlSzu9tkq1atYsQuPGpXjxxTrs2dObNm1CtFAgDUnsTOddoAK2zUxz7Jw1dbGzfHYBvgBKG2P66T0dlWblz28Hlx49ap/Xr4e6daFxY/jpJ20umgqEh5+nbduv2b/f/pkRERYvfpKRI5uSI4c250xrEks6jYE3jTHDjTFLjDETgI5ATWCMMaazMeZPr0SpVErLndtOn3D0qD0D2rPHJp5774VFizT5OCAy8ibvvbeaihXHMWfOnn9MrJYp0x3fjlYOSew3VwBYH2dZzHWHWSkTjlIOy5YNXnrJ3vOZMAFOnLCX3GrWhG++0c7WXrJ69TFq1JhI//7LuHo1iscfr8z48dr4JD1ILOn4AHE7KMZ8fyVlwlEqlciSBXr2tNVuU6bA5cu22KByZdvpOirK6QjTpYiIK3TrtoD77vucXbtOU6ZMHr7/vj0zZrSlcOHsToenPCCpc9QHRKRLzAPojJ2OoFXs5a7XlEp//PygY0fYvduO9/Hzs2XWwcEwaRJcv+50hOnK2bNX+fLL7fj5+fD66/XZseMZnTo6nUmwy7SIJOc6gnFnPh2naZdpdceMgYULbdHBhg1QrJidXvvppyGrjn6/HYcPn6NUqdy3KtC+/HI7oaFFqVAhv8ORqRje6jJdKhmP0gnsQ6n0RQQeeMBWuf3wA5Qta1vrBAXZyeUuXnQ6wjTj6tVIBg5cRoUKY5k+fcet5e3bV9WEk44lmHSMMUeT8/Bm0Eo5TgT+8x9YscJ2t65Z0zYVDQy0TUYjdBRBYpYsOUjlyhMYPnw1kZHR7N592umQlJdo3aFSd6pePVi8GDZtgkaN7HQKgYF2eoWTJ52OLlU5ceIvHn30G5o1m87hw+eoUqUga9d2Yfjwxk6HprxEk45SnlKzJsyZAzt2QOvWdrxPqVJ2Yrljx5yOznEbN/5OhQpj+frrXWTN6seIEfezeXN37rmnhNOhKS/SpKOUp1WuDNOnw7598OSTMHGivffTrRscPOh0dI6pWrUQRYvmoFWrYPbs6c3LL9fFzy/V1x8pD9Oko1RKKVsWPv3UJpoePWwiCg62iWjXLqejS3EXLlyjX78fiIiww/r8/X1Zu7Yr8+c/RsmSuRyOTjlFk45SKa1kSRgzBo4cgb59YcECezbUpg1s3ux0dB5njOHrr3cREjKOESPWMmDAsluv5c0b4GBkKjVIVtIRER8RqSwiDUQkW0oFpVS6VLgwvP8+hIfD4MGwfDmEhkKzZrB6tdPRecThw+do3nwGjz76DX/8cYk6dYrTu3ctp8NSqYjbSUdEegMngW3AT0Cwa/k8EXkuZcJTKh3Klw+GDLHNRd95x57t3I/DMxcAACAASURBVHcfNGxox/6kweaiN27cZPjwVVSqNJ4lSw6SO3cWJk5syZo1XahWrbDT4alUxK2kIyJPA6OBecCjQOzJK1YBbT0fmlLpXM6c0L+/PfMZNcre+2nSBOrUsZfg0lDy2bTpBAMH/sS1a1G0b1+VvXt70717TXx8dJ4b9U/unum8BHxojOkOxJ2aei+usx6l1G3ImtXOYnrokK10O33allxXrw4zZ8LNm05HGK/Ll//uB1y3bgkGD67PsmUdmDbtIQoV0uacKn7uJp1SwPcJvHYZ0HlilbpT/v7QvTvs3287Wd+4AY89BhUr2k7XkZFORwhAdLRh8uQtBAaOYuXKv5uRDBnSiLCwUg5GptICd5POGSAogdeCgd89Eo1SCnx9oX17W1Y9a5Y9E+rcGcqVs3P8XLvmWGg7d56iQYMpdOv2LRERV/m//9uR9EZKxeJu0lkIDBaR2I09jYjkB17E3utRSnmSjw88/DBs2WI7WxctCr16QenSMHKknePHSy5fvkH//j9So8ZEVq8+RqFC2Zgxo41OrKaSzd2kMwi4DuwEfsTOqfM/YA9wE3jL3QOKSAkR+UZELojIRRGZIyIlk7F9iIjMEpEzInJVRPaJyPPubq9UmiMCLVrAmjXw008QEmLH+wQGwrBhcOFCih7+11//oFKl8bz33hpu3ozmmWdC2bu3D48/XuXWdARKucutpGOMOQOEAu8AfsAhwBcYC9xjjHHrX72IZMWWW1cAOgJPAeWA5e6M+xGRUOAXwB/oBjQHPgS0l4ZK/0RsQ9Fly2DtWlvlNmiQTT6DBsGZMyly2JIlc3Hp0g2qVy/MunVdGT++BblzZ0mRY6n0L8FJ3FLkYPaMZCQQbIw56FpWCjgA9DPGjExkWx/smdY+Y8xDt3N8ncRNpTu//grDh8Ps2RAQYKfY7tvXXoq7TVFR0UyZspWnnqqKv78vALt2nSI4OD++vtrEJCPy1iRusQ/4kYhU98DxWgHrYxIOgDHmCLAGaJ3Etg2BEGzSUkoB1Khhiw127YK2bWH0aNvZulcvO/4nmTZs+J1atT7h6ae/ZcSItbeWV6pUUBOO8gh3/xV1AjaLyE4R6ScixW7zeJWwZytx7QIqJrFtPddzFhFZLyKRInJKRP4nItrQSWVsISHwxRe23LpTJ9totFw5W/W2f3+Sm58/f43evRdRp86nbN16kpIlc1GjhnYSUJ7nbtIpBLQDDgJvA0dF5EcR6ZDMHmx5gXPxLD8L5Eli25jrBTOBpcD9wPvYezszkhGDUulX6dJ2gOnhw9C7tx1cWqGCHe+zffu/VjfG8NVXOwkJGcf48ZvIlMmHfv3qsnt3L1q0KO/AD6DSO3cLCW4YY2YbYx4EigDPAQHAFOBPEZmWciHeEhPrl8aYwcaYFcaYD4AhwIMiEhLfRiLSXUQ2icim06d1SlyVQRQvblvrhIfDq6/Cd99BtWq208GGDbdWW7r0EI8/PpuTJy9Rt24Jtmzpznvv3U+2bJmdi12la8m+SGuMOWuMGW+MuRdohD1zecLNzc8R/xlNQmdAscVMOv9DnOVLXc814tvIGDPJGBNqjAktUKCAm2EqlU4ULGibih49apuMrl6NqV3b9nhbuZImTcrw8MMV+eSTB1i1qjNVqhRyOmKVziU76YhINhHpKCI/YMfs5Admu7n5Lux9nbgqArvd2DYx0W7GoFTGkycPDB7M8i9WUqPIEA5sOQoNGiD16zOraw66da2hzTmVV7hbveYjIv8VkenAn8Bn2LEyzwCFjTHt3DzeAqBO7M4GIhIE3Ot6LTGLsQNUm8ZZ/l/Xs9ZCK5WAU6cu06HDXMJafsO2PwzvP/CunVju6FE7n0+tWjB3LkTrZzeVstw90zkBLMIOEH0XKGOMqW+M+dTdgaEunwDhwHwRaS0irYD5wG/AxJiVRCRQRKJEZHDMMmNMBHZwak8RGS4i/xGR/sBgYGrsMmyllBUdbfjkk81UqDCWadO2kyWLL0OHNmLsxw9Anz52OoVPP7VdDdq0gapVYcYMiIpyOnSVTrmbdL4B6hpjgo0xQ40x4bdzMGPMZSAM2A9MA6YDR4AwY8ylWKsKtstA3PjeAvphK+m+w55pjQCevp14lErP9u07Q716n9G9+0LOnbtGkyZl2LnzGQYOrH9r0CeZM0PXrrBnD0yfbpc9+aQtwZ482Xa6VsqDvNqRwGnakUBlJAcORFClygTy5Alg1KimtGtXKeleadHRMH++7em2eTOUKAH9+tnEFKDD4TIqT3YkSDDpiEh9YIsx5pLr60QZY1Z6IqCUpElHpXcrVx7lvvtK3kouixcfoG7dEuTKlcxeacbA99/b5LN6NRQqZNvr9OwJOXKkQOQqNfNW0okG6hhjNri+TuiUSABjjEn1TTc16aj06rffLvDss4uZP38f06Y9RPv2VT2385UrYehQ+OEHyJvXznL67LO2Ik5lCJ5MOr6JvNaIv8uYw0g46SilHBIVFc3//vcLgwcv5/LlSHLkyMyNGx6e3rp+fVi61A4qHTYM3ngDPvjAdjx48UU7FkgpN+k9HaXSqPXrj9Oz50K2bfsTgIcfrsioUU0pVixnyh54+3bb2frrryFLFjvF9ssv2y4IKl1yosv0YRGplsBrlUXksCeCUUq557vvDlC37mS2bfuToKDcLFr0BLNmPZLyCQdsWfVXX9mKt0cfhXHjbM+3Hj1szzelEuFuyXQQdjBofLIAgR6JRinllsaNS1G5ckEGDKjHrl29aN68nPeDCA6Gzz+HAwegWzeYMgXKl4cOHWxCUioeyWmDk9B1uFDgvAdiUUolYP/+CNq1m0VExBUA/P192by5O8OHNyZrVj9ngwsKgvHj4cgRW2QwezZUqgSPPAJbtzobm0p1Ekw6IvKiiBwTkWPYhPNtzPexHqeBccASbwWsVEZy7VoUb765gipVJjBr1m6GDPn51mt+fqmsYLRoUfjwQ9ta57XXbPFBjRrQsiWsW+d0dCqVSKxkujXwoOvbjtgOAHHnBriOrXD71BhzJaWC9BQtJFBpyY8/HqZXr0UcOHAWgC5dqvPee/eTP39WhyNz0/nz9n7PRx9BRASEhcGgQdCwISQ1SFWlKl4ZpxPngJ8Db7mmlk6zNOmotODkyUv07buUGTN2ABASkp+PP25J/fpp9Nbp5ct2YrkPPoA//oB77oGBA6F5c00+aYTXq9eMMZ3TesJRKq3Yvz+CGTN2kCWLL8OHh7F1a8+0m3AAsmWDl16ylW3jx8OJE/aSW82a8M032tk6g0ns8tpg7GWzE7G7PSfAGGPe9nh0HqZnOiq1On78IsWL/13u/L///ULLluUpXTodjvqPjLTNRd95B/bvt81FBwyAxx8H38TGqyunONUGJzHaBkep23Dp0g0GD17OmDEbWLasQ9o+o0mumzftmc7w4XbAaenSdmrtjh3BP6ERGsoJXrm8ZozxMcZsiPV1Yo9Un3CUSk2MMcybt5eQkHF89NF6oqMNGzb87nRY3pUpkx1cunUrLFgA+fPbAaZlysDo0XAl1dcmqduQ7OmqlVJ35ujR87Ru/RUPPTST48cvEhpalA0buvHyy3WdDs0ZIvDAA7B+vS2zLlsWXnjBjv959124eNHpCJUHudsGp7yI3B3r+wAReUdEvhWRPikXnlLpy/ffH6RixfF8++1+cub0Z+zYZqxf35WaNYs6HZrzROD++2HFCli1yhYaDBgAgYG2yWhEhNMRKg9w90xnLPBwrO+HAX2BosBHItLb04EplR6FhhYla1Y/Hn20Env29KZ377vJlEkvOPxLvXqweDFs2gSNGsFbb9nk068fnDzpdHTqDrj7r70asAZARHyADsCrxpiawFCge8qEp1TadvbsVQYN+onr16MAyJcvKzt3PsNXXz1M0aI6GVqSataEOXNgxw5o3dp2PChVys7nc+yY09Gp2+Bu0skFxJzb1gDyAN+4vl8BlPZsWEqlbcYYvvhiG8HBYxk2bBUjRqy99VqhQtkdjCyNqlzZllnv2wdPPmkHm5YtaxuNHjzodHQqGdxNOn8CZV1fNwEOGWN+c32fHYjydGBKpVV7954hLOwLOnacx5kzV2jQIJC2bUOcDit9KFsWPv3UJpoePWwiCg62iWjXLqejU25wN+ksAN4RkQ+w93JmxXqtCqCTaKgM7+rVSF5//SeqVp3AihXh5M+flSlTWrN8eUdCQgo4HV76UrIkjBljO1v37Qvz59uzoTZtYPNmp6NTiXA36fQHFgJNsQloeKzXWgFLPRyXUmnOt9/uZ+jQVURGRtOtWw327u1Nx47VEe0vlnIKF4b337edrQcPhuXLITQUmjWD1audjk7FQ6erVuoOXLsWRZYstnWLMYZevRbx5JNVqVevpMORZVAXL9r+biNHwunT0KCBbS76n/9oc9E74PWGn7EOnFdEWojIU67nvJ4IQqm05ubNaMaN20Bg4CgOHLA1NiLChAktNeE4KWdO6N8fwsNh1Ch776dJE6hTB779FjLQh+zUyu2kIyJDgd+Bb4GpruffRSTVN/pUypO2bPmDe+6ZTJ8+izl16jLTp+9wOiQVV9asdhbTQ4dspdvp09CqFVSvDjNn2r5vyhHudiR4AXgN+BJoBIS4nr8EXhOR51IsQqVSiYsXr/PCC0uoVesTNm48QbFiOZgzpx1vvNHA6dBUQvz9oXt32836iy/gxg147DGoWBGmTLEdr5VXuTuJ215gsTHmxXhe+whoZoypkALxeZTe01G36+efw3niiTmcOPEXPj7C88/XZsiQhuTIod2Q05ToaDvYdNgw22g0MNB2tu7cGbJkcTq6VMuJezpBwKIEXlvkel2pdKtIkRycOXOFu+8uxqZNTzNyZFNNOGmRjw88/DBs2QILF0KRItCrl51WYeRIO8upSlHuJp0IoHICr1Xi724FSqULN27cZNq0bcRcCShfPh9r1nRh7dou1KhRxOHo1B0TgRYtYO1aWLbMTiTXt6/tbD1sGFy44HSE6Za7SWcu8Laras0XQER8ReRx4C1gtrsHFJESIvKNiFwQkYsiMkdEkl3uIyL9RcSIiBbjK49ateood901kQ4d5v2jSCA0tKg250xvRCAszCaetWuhdm0YNMhedhs0CM6ccTrCdMfd/0EDgK3YqrWrIvIncBWYDmzDFhkkSUSyAj8BFYCOwFNAOWC5iGRzN2gRKQ0MAk65u41SSTlz5gpdu86nfv0p7Np1mrJl81KsmDblzDDuucdectuyxU6xMHy4TT59+8IffzgdXbrh9uBQscOqWwD3AXmBs8DP2AIDt3YiIs8DI4FgY8xB17JSwAGgnzFmpJv7+R4IB4IBX2NMPXe200ICFR9jDFOnbuPll5cSEXGVzJkz0b//vQwYcN+tgZ8qA9qzB955B2bMAF9f6NLFTq0QFOR0ZF7nyUKCRJOOiOQH2mObfZ4DZhtjtt72wUSWAVmMMffGWf4zgDEmydpTEXkCGI1NOHPQpKPu0Oef/0qXLgsACAsrxfjxzQkOzu9wVCrVOHwY3nsPPv/cDi5t395OLle+vNOReY1XqtdEJBjYhT0z6QUMBDaKSOs7OF4lYGc8y3cBFZPaWETyAB9hz4rO3kEcKoOL/WHriSeqUL9+INOmPcSPPz6lCUf9U+nSdoDp4cPQu7cdXFqhgh3vs32709GlOYnd0xkKXAMaAtmw3aQ3YJPQ7cqLPWOK6yx2jp6kjAD2A1PcPaCIdBeRTSKy6fTp0+5uptKxxYsPUKfOZCIirgDg7+/LihUdad++qjbnVAkrXty21gkPt2N7vvsOqlWzk8tt2OB0dGlGYkmnNjDYGLPSGHPVGLML6AEEiYjX+7SLyH3YGUufcfceEoAxZpIxJtQYE1qggLaXz8hOnPiLdu1m0bz5DDZs+J3//e+XW69pslFuK1jQ3us5ehSGDIFVq2zVW5MmsHKl09GleoklnWLAvjjL9gECFL3N450j/jOahM6AYpsITAaOi0huEckN+AKZXN/rSD0Vr5s3oxkz5hcqVBjLrFm7yZrVjw8+uJ9Bg+o7HZpKy/LksdMpHD1qp1fYvt12tb7vPliyRJuLJiCxpCNA3K540W5sl5hd2Ps6cVUEdiexbQjQE5ucYh73AnVcXz9zmzGpdGzr1pPUrv0pzz23hL/+ukHr1sHs2dObvn3r4ueXyenwVHqQIwe88oqdUG7MGJuEmjWDWrVg7lzbekfdklQ96BARiT06KuYaxNsiEvtGvjHGdHTjeAuAD0SktDHmMICIBGGTR/8ktm0Uz7JRQCbgWUAnSlf/cuHCNTZv/oMSJXIyZkwzWrdO9S0CVVoVEAB9+tgGo9Om2UtwbdpApUrw2mvQrp0tvc7gEiyZFpFwwN3zQ2OMKZ3kwewA0G3YgaWDXPt/G8gBVDXGXHKtFwgcAt4yxryVyP5WoCXTKhZjDJs2naBWrWK3ls2cuZMWLcqTPXtmByNTGU5UFHz9tR1kumsXlC1r5/p56inInLb+LXqlZNoYE2SMKeXmI8mE49rnZSAMW4E2DdvR4AgQFpNwXAR7BqM9R5TbDh8+R/PmM7j77k9ZufLoreWPPlpZE47yPl9feOIJe69nzhzIlQu6dbPJZ+xYuHrV6Qgd4fU/6saYY8aYtsaYnMaYHMaYB40x4XHWCTfGiDHmzST21dDdsxyVfl2/HsWwYSupVGk8S5YcJHfuLJw6pd2CVSrh4wMPPQQbN8LixVCyJDz7LJQqBSNGwF9/OR2hV+mZhErTfv45nOrVJzJo0HKuXYuiffuq7NvXh4cfTnKssVLeJQL//a8tsV6xAqpW/butzltvwbmkCnjTB006Ks36/PNfadhwKnv3nqF8+XwsW9aBadMeomBBt3vHKuV9Ira0eulS+OUXqFcP3njDNhcdMABOpe8+xpp0VJrVqlUwxYvnZMiQhmzf3pOwsFJOh6RU8tx9N8yfD9u2QfPmtsdbUBC88AIcP+50dClCk45KM3buPEXHjvO4fj0KgHz5snLgwLMMHtwAf38tRVVpWNWq8NVXtrP1o4/aQoMyZaBHD9vzLR3RpKNSvcuXb9C//4/UqDGRL77Y9o/2NTr1gEpXgoNtN+uDB6FrV5gyxXaz7tDBJqR0IFlJR0SqikgfEXlDRAq7lpUVEZ3pSqWIRYv2U6nSeN57bw03b0bTq1coTz9d0+mwlEpZQUEwfrztcvD88zB7th1k+sgjsPW2Z5dJFdxKOiLiLyKzgF+B/wGD+bv/2vvYaQ+U8pjjxy/Stu3XtGz5fxw9eoHq1Quzbl1Xxo1rQe7cWZwOTynvKFoUPvzQttZ57TVbfFCjBrRsCevWOR3dbXH3TGcY8B/s9NKF+LsdDsBioKmH41IZ3PLlR5gzZw/ZsvkxcmQTNm58mtq1izsdllLOyJ8fhg61yWfoUFi/HurWhcaNYfnyNNVc1N2k8zgwyBgzAzv3TWxHgCBPBqUypj///LspRfv2VXnzzQbs2dObF1+8B19fvf2oFLlzw8CBdk6fDz+093nCwuDee2HRojSRfNz9n5wPSOgulg+g0wqo23b+/DV69VpEqVKjOXAgArDz27zxRkNKlMjlcHRKpULZs8NLL9nKtvHj4cQJe8mtZk345ptU3dna3aRzBLgngdfu5t/z7iiVJGMM//d/O6hQYSwTJmwiMjKa1auPOR2WUmlHlizwzDNw4ICtert82RYbVK4MX35pm46mMu4mnS+A/iLyJODnWmZEpBHwIvBZSgSn0q8DByJo2vRLnnhiDn/+eZl77y3Bli3d6dy5htOhKZX2+PlBp06we7cd7+Pra7tZBwfDpElw/brTEd7ibtJ5H1iE7Qwd0yBoNfAjsMQYMyYFYlPp1IwZO6hSZQI//HCYvHkD+PTTB1i5sjNVqhRyOjSl0rZMmezg0q1bbaeD/PntANMyZWD0aLhyxekI3Us6xpibxpjHgAbAh8Cn2NLpMGPMkykYn0qHQkNttX3HjtXYu7c3XbvehY+PJLGVUsptPj7QqpWtclu61E6n8MILdvzPu+/CxYuOhZbgJG7pkU7i5oxTpy7z2We/8uqr9yJik8vx4xcpXjynw5EplYGsXg3DhsGSJbYKbsQIO7+PG7wyiZtSdyo62jBp0maCg8cyYMAyvvxy+63XNOEo5WX16tn5fDZuhHLloG9fR0qs3e1IEC0iNxN7pHSgKm3Zvv1P6tX7jB49FnL+/DWaNi1D3bolnA5LKRUaCl262Etsv/3m9cO72y3xLSBuSswHNMGO0ZniwZhUGnbp0g2GDFnBRx+t5+ZNQ+HC2Rk9+r888kjFW5fWlFIOq1zZPu/caWcy9SK3kk5C00aLSCbgW+CCB2NSadikSZv54IN1iECfPrUYOjSMXLm0V5pSqUpM0tmxw87j40V31BfeGHNTRMYDY4FRnglJpTWRkTfx88sEQO/etdiw4XdefrnurSo1pVQqkzs3FC9uz3S8zBOFBP5AXg/sR6UxkZE3+eCDtZQvP5aICFv/7+/vy1dfPawJR6nUrkoVe6bjZW6d6YhIfBf9MgOVgXcBrUPOYNavP06PHgvZvv1PAGbN2k3Pnh6pqFRKeUPlyrBsmW2V4+u9yRDdPVI4/y4kADvFwSGgt6cCUqnbuXNXGTBgGZMmbcYYKFUqN2PHNqd583JOh6aUSo4qVeDGDdu3LSTEa4d1N+l0jmfZNeAosNEYoyXTGcDChfvp2nUBp05dxs/Ph1deqcvAgfXJmtUv6Y2VUqlLlSr2eceO1JV0XBVqW4ETxpjTKR+SSq1y5vTn1KnL3HdfST7+uCUVKxZwOiSl1O2qUMH2atu5E9q189ph3SkkMNh7Ntr+N4O5di2KefP23vq+fv1AVq7sxM8/d9KEo1RalyWL7Uzg5WKCJJOOMSYa+A3IlvLhqNTihx8OUaXKBB56aCYrVx69tfy++wJ1kKdS6UXlyl4vm3a3ZHoi8IKIZE7JYJTzTp68xBNPzKZJky85ePAsFSsWwN8/k9NhKaVSQpUqcOiQnfzNS9wtJMgBlAEOi8gS4A/+Wc1mjDFvuLMjESkBfATcj61++xF4wRiT6JSRIhIKdAfqAyWBM8AqYJAx5oibP4dKwM2b0UyatJkBA5Zx4cJ1AgJ8GTy4AS+9dA+ZM2vSUSpdqlzZNv3cs8f2ZPOCBJOOiBwGHjLGbANei/VSl3hWN0CSSUdEsgI/AdeBjq7thgLLRaSqMSaxdPsYUAk7j88uoBjwOrBJRKobY7zfuS4deffd1QwatByAZs3KMm5cc0qVyuNwVEqpFBW7gs3ppAMEYbsNYIzx1BQITwOlgWBjzEEAEdkOHAB6ACMT2fa9uNVzIrIGOOLa72APxZgh9ewZyqxZu3n99fq0aROi922UyghKl4aAAK/e1/H2fDqtgPUxCQfAdWlsDdA6sQ3jK9c2xhwFTmPPepSbjDHMnbuH+++fxvXrUQDky5eVX3/tQdu22g1aqQwjUyaoWNGrFWxJJR1Pz/BTCYgvpe4CKiZ3ZyISAhQE9txhXBnG0aPnadXqK9q0+ZoffzzMlClbb72myUapDMjLFWxJFRIMEZEzbuzHGGM6urFeXuBcPMvPAsm6gSAivsDH2DOdyYms1x1bgEBJL88bkZpERt7ko4/WM2TIz1y5EknOnP4MHx5Gt253OR2aUspJVarA1KkQEQH58qX44ZJKOtWxN/2T4v05T+10CnWBFsaY+BIZAMaYScAkgNDQUCfidNy6db/RvftCdu48BcCjj1Zi5MimFC2aw+HIlFKOiz23TsOGKX64pJLOg8aYDR483jniP6NJ6AwoXiLyLvbspaMxZqmHYku3Dh48y86dpyhdOg/jxzenadOyToeklEotYirYdu5MFUnH03Zh7+vEVRHY7c4ORGQg8CrwrDFmmgdjSzeMMezceYoqVQoB0L59Va5di6J9+6oEBGhzTqVULEWKQN68Xism8Hb12gKgjoiUjlkgIkHAva7XEiUiz2HH9Qw0xoxNoRjTtD17ThMW9gW1an3CgQMRgC0QePrpmppwlFL/JuLVYgJvJ51PsHPzzBeR1iLSCpiP7e02MWYlEQkUkSgRGRxr2WPYKbGXAD+JSJ1Yj2RXvqU3V69GMmjQT1Sr9jErVoSTI4c/4eHnnQ5LKZUWVKlik45J+dveYrxwkH8c0M5CGrsNzjJsG5zwWOsEYQd9DjHGvLlly5amx48fn+br61vAx+ffedLPz+96/vz5TyZ17IiIiMAiRYp45OdITa5ejeTs2atERUUDkD17ZvLkCcDHR0uglVLx8/X1JUuWLBQoUIAsU6bAM8/A0aMQT5WviGw2xnikZYG37+ng6rHWNol1wrEJiS1btjT19/cf27hx49MBAQG/+fj43HaW3L17d2CIFycr8oY//viLy5f/InduCAjwJTAwF9mz+zsdllIqFTPGEBUVxaVLlzh27BiFqlUjF9j7Oik8tMTbl9eSzdfX942goKAb2bJlu3onCSe9ypMngEyZhOLFcxISUkATjlIqSSKCn58fefLkoXjx4kTkzWtf8MJ9Ha+f6SSXMaZwQECA2+XU6d3lyzeIiLhKiRI5ERGyZPGlatVCZMqU6j8/KKVSoYCAAK5HR0OJEl6pYEv1SQfw0TMcO/XA77//xalTthF39uyZyZs3AEATjlLqtt1qf+WlCra0kHQyNGMM585d47ffLhAZaQsFChXKRq5cehlNKeVBVarAsmUQGQl+KTe8QpNOKnb9ehTHjl3gwgXbiShbNj8CA3OTNauOt1FKeVjlynDjBhw4YDtPpxC9LpOKnT17lQsXrpMpk1CyZC4qVMivCUcplTJit8NJQZp0vGzKlCmIyK1Hjhw5qFatGmPHjiUqKurWWBuAQoWyU6hQNipXLkjBgtk8OvVAeHg4IsKUKVOSHXt4eLjH4nBHp06d/vGeZc2albvuuovPPvvMq3HEJygoiE6difT5DQAAIABJREFUOt363qn3yGnPPfccLVu2dDoMR/322288/PDD5MqVi5w5c9KmTRuOHTvm1rax/33HfmzduvUf6505c4YuXbpQoEABAgICqF27Nt9///0/1rl69SpFihTh66+/Tt4PUKGCnV8nhYsJ9PKaQ2bNmkXx4sW5ePEis2bN4tlnn2X//mN06fISlSsXwNc3Ez4+QokSuVLk+EWKFGHdunWUKVPG7W1atGjBunXrcGKAbYECBViwwHZK+vPPPxk9ejRdu3YlV65ctG2b6LAvlcIOHTrExx9/zNq1a50OxTFXrlwhLCwMf39/pk6diogwaNAgGjVqxPbt28mWLVuS++jUqRM9evT4x7Ly5cvf+vr69euEhYVx5swZ3n//fQoXLszkyZNp2bIlP/zwAw1dzToDAgLo168fr732Gg899BB+7t6fyZIFypVL8TMdTToOqV69OmXLlsUYw1131WPr1t189tnHdOz4ApcuRZI7d6Z/rB8ZGYmvr6/Hznb8/f2pU6dOsrYpUKAABQoU8Mjxkytz5sz/iLdx48aUKFGCTz75RJNOPK5fv46/v3eKTUaNGkW1atUIDfXIgHWvxu4pn3zyCYcPH2bfvn2ULWu7uFetWpVy5coxceJEXnrppST3UaxYsUT/T86aNYsdO3awfPnyWwnmv//9L9WqVaNfv35s2PD3hACdOnWif//+zJ07l3bt2rn/g1SpAlu2uL/+bdDLaw66ejWSffsiCA8/T0hINS5f/osCBeD8+ZOICOPHj6dfv34ULVoUf39/zp+3vdT+v70zD4+qyBb47yQBEiaBBKLDTtiDrKJEBCGojCDK4sqTZQLijE9BlGF8joYliAw4iDjuwiBocBkV9BHx4fJGwA0FIzDsO2iAxw6RJWQ574+63XR3OkmTdDpE6/d990u6bi3nnr5d51bVuacWLVpEly5dqF69OrGxsdxxxx1+h/Fz5syhU6dOREVFERcXR3Jysvtp1N/02qpVq/jd735H7dq1iYqKomnTptx///3u8/6mjnJzcxk/fjwJCQlUrVqVhIQExo8fT25urjuPq61XXnmFiRMnUrduXWJjY+nXrx8//fRTqXQXHR1Ny5YtC133rl27GDJkCJdccgnVqlWjY8eOvP/++4XKr127lltuucV9ra1atWLatGnu85988gl9+/albt26VK9enbZt2zJz5kzy8/NLJa8/3n//fbp160Z0dDQ1atQgKSnJPZoravpz2bJliAjLli1zp/Xs2ZNrrrmGjIwMLr/8cqpVq8aLL75ImzZtuPXWWwu1+9133yEiXnpZu3Yt/fv3Jy4ujqioKLp168YXX3xR4jXk5OSwYMECBg8e7JV+9uxZxo4dS9u2bYmOjqZOnTr069ePzZs3e+Vz3VMrVqzgjjvuIDY2lquuugqAvLw8pk2bRmJiItWqVaNevXqMGzeOs2fPetUxadIkOnXqRI0aNYiPj+e6665j5cqVJcoeTBYvXkyXLl3cBgegSZMmdOvWjf/+7/8OShsrV64kKirKbXDATMvdcMMNrFq1iqysLHd6XFwcvXv35h//+MeFNdK2LezcCadOBUVmf1Tekc7ddzdk/frqF1KkMUD1CypSPB07wjPPlKrokSOnOXHiEKoQERHGiRMHCA8PJz4+loMHzWZrU6dOpXPnzsyePZv8/HwiIyN5+eWXue+++xgxYgQTJ04kOzubtLQ0kpOTWbduHTExZmO2P//5z8ycOZORI0cyefJkwsLCWLlyJXv37qVr166F5Pn555/p3bs3SUlJzJ8/n5iYGHbv3l3ilElKSgrvvPMOjz32GNdccw1ff/01U6dOZefOnbz55pteeadNm0bXrl159dVXOXjwIOPGjWPo0KFeHWig5Ofn8+OPP3LFFVe403788UeuuuoqLr30UmbNmsUll1zCP//5T2677TY++OAD+vfvD5hOt2fPnjRv3pxZs2bRoEEDtm3bxrp169x17dy5k+uvv54HHniAyMhIVq9eTVpaGocOHWL69OkXLK8vzz33HGPGjGHgwIG89tprREdHk5mZWeq1oK1btzJmzBgmTJhA06ZNqVWrFjk5OaSlpXHs2DHi4s5vY5Wenk6tWrW46aabAMjMzKR79+5cfvnlzJkzh+rVq/Pyyy/Tq1cvvv76ay8d+7Jy5UqOHz9O9+7dvdJzcnLIzs5m/Pjx1K1bl6NHj/Liiy9y9dVXs2nTJurUqeOVf8iQIdx1112899575OXlATB06FAyMjJ45JFH6Nq1K5s2bWLChAns3r2bhQsXustmZWUxduxYGjRowKlTp1iwYAE9evTg+++/p51rcbwI8vPzCST+ZERE8V3lhg0bGDBgQKH0Nm3a8O6775ZYP8BLL73EjBkzCA8Pp0uXLkyePNlLr+Hh4X6nylyjwvXr11O/fn13eo8ePUhNTeXs2bNERkYGJAPt2pmgnxs3QufOgZW5UFT1oj7WrFmzW1VXFzpGjPg/7dw5+0KOnzt3Vk1ODt7x4IN6ocybN08B/f77dfrNN3t07dpd+sILL2pYWJgOGDBAVVV37dqlgF5++eVaUFDgLpudna01atTQESNGeNW5c+dOrVKlis6aNUtVVbdt26ZhYWE6duzYIuVwtTFv3jxVVV21apUCunbt2hJl37Vrl6qq/vvf/1ZAJ02a5JVvypQpXnW52kpOTvbKN2PGDAU0KyuryDZVVVNSUrR+/fqam5urubm5mpWVpaNHj9bq1avrypUr3fnuvvtujY+P18OHD3uV79Wrl3bo0MH9uXv37tqgQQM9depUse26KCgo0NzcXH3iiSc0NjZW8/Pz3ecaN26sKSkp7s++OvLHiRMnNDo6Wm+55ZYi8/h+Py4+//xzBfTzzz93pyUnJ6uI6A8//OCVd+/evRoWFqYvv/yyO+3cuXMaHx+v9913nzvtuuuu08TERM3JyXGn5eXlaWJiovueLIrp06eriHiV9UdeXp6eOnVKo6Oj9emnn3anu/T10EMPeeVfsWKFAvraa695pS9YsECBQtfq2U5ubq62bNlSx4wZU6xMqub7w+x8XOxR3PepqlqlShV95JFHCqWnpqZqeHh4iXIMHTpU3377bV2xYoWmp6dr+/btNSIiwut7fuGFFxTQjRs3epW99tprFdA333zTK/2zzz5TQL/66qsS23fXuXWrKqi++qrXeWC1BqlPr7wjnVdf/fFCi+zZuPGKy8rR/7w4zp3L58SJ89MCV1zR3v1/WFgYQ4YM4RmfUdPAgQO91nC++eYbTp48yZAhQ9xPgwANGzYkMTGRFStW8NBDD/HZZ59RUFDAH//4x4Dla9GiBbGxsdx7772MGjWK5ORkGjZsWGyZFStWAOaJ1JOhQ4cyYcIEli9fTvv256+zb9++XvlcT6F79+6lXr16xbaVlZXl9ZQnIrz11lvuqRiApUuX0rdvX2rWrOmln969e/Pwww9z8uRJIiIi+Oqrr3j44YepXsyod//+/aSlpbF06VL27dvnVd/BgwcLPalfCF9//TU///zzBX0/JZGQkEDHjh290ho2bEjPnj1JT093L1AvXbqUw4cPM2zYMMB4Oi1fvpzHHnuMsLAwr+vs1asXb7zxRrHt7tu3jxo1alC1atVC59555x1mzpzJli1bOHHihDt9y5YthfLecsstXp+XLl1K1apVuf32271kuuGGGwBz77mu97PPPmPq1KmsW7eOo0ePuvM2adKkWNkBMjIyyMnJKTFfSfdnWUlPP78fZffu3RkwYABt27Zl/PjxfPnllwAMHjyYSZMmkZKSwty5c6lbty6zZ892/w59I/C71l/37dsXuCBNm0JUVLl6sFVeo1NJUFUOHjxFVlY2BQXK2bNmreP999+nQYMGxMTE0LhxY7/DX18vMde0W69evfy25ZpCOXLEbN7WoEGDgOWsWbMmn3/+OVOmTOH+++8nOzubNm3aMHny5CIX6l0/cF85XR2yZwcAUMsVVNDBNS3gO0fvj0svvZQlS5ZQUFDAjh07GD9+PHfffTcdOnQgMTERMPp5/fXXef311/3WceTIEapWrUpBQUGxuikoKKB///7s27ePtLQ0EhMTiYqK4oMPPmDq1KkByVscpfl+SqIoj8Jhw4YxYsQIdu3aRZMmTUhPT6d58+ZcffXVgPmO8vPzmTJlClOmTPFbR0FBQaEOzcXZs2f9LvpnZGQwaNAgUlJSmDRpEvHx8YSFhdG3b1+/+vN3r587d65Iry+XDjMzM+nbty+9e/d2d8Th4eHcc889AX1Pl112WVCm1+Li4jh2rHCIyKNHj3pNbQZKTEwMN910E3PnznWnxcbGsmjRIlJSUtwPc82aNSMtLY0JEyYU0mFUlAmTdebMmcAbDg83L4aWowebNTrlyKlT59iz5wSnTxtDExsb6Y6T1rZtW69FR3/4eqrVrl0bMIuvbdoU3vXbtZ4THx8PmNFBq1atApa3Y8eOLFy4kLy8PFavXs20adO48847Wbt2LW3bti2U32VEDhw44OV6feDAAa/zwaBKlSpu76ikpCQ6depE+/btGTduHEuWLAGMfrp3784jjzzit4569eqRn59PWFiY16KrLzt27GD16tWkp6d7jeIyMjKCci2e348/vQLuh5Bz5855pbs6W1+K8mq87bbbGDVqFAsWLGDMmDFkZGTw6KOPus/HxsYSFhbGqFGj+P3vf++3jqIMDhiduxxcPHn77bdp3ry5lyNEbm5uoQeRouSvXbs2kZGRRTozuEYeCxcuJCIigkWLFnmNhI8dO0ZsbGyRcrto1qwZe/bsKTHfrl27SEhIKPJ8mzZt2LBhQ6H0jRs3UpbZFV+9dO/enR07drB9+3by8/Np2bIlM2bMICoqqtDam0vXrvstYNq1g6VLSy1zSVijUw7k5RWwb9/54JxVq4bTqFFNYmMj+fLL8BJKF03Xrl2JiYlh+/btpKSkFJmvV69ehIWFMXv2bGbOnHnB7URERNClSxemTJnC4sWL2bRpk9/OsUePHoDpYFJTU93prikZTy+bYNOqVStGjRrFrFmzWLVqFZ07d6ZPnz588803tGnTxv2U549rrrmGBQsWMHHiRL/5Tp8+DeDVieXm5pY41RQoXbt2JTo6mtmzZ9O7d2+/eX77299SrVo11vs8cboMbKDExMQwcOBAFixYQL169cjJyfEypL/5zW/o3r07a9eupVOnTsUaGH8kJiZy7tw5fvrpJ6+R2+nTpwuNDtLT0wP2/uvTpw9PPvkkJ06c4Prrry8y3+nTpwkPD/fqnP/1r3+xd+/ekE6v9e/fnz//+c/s3LmTpk2bAsYD8auvviqV48nJkyf58MMPSUpKKnRORGjRogVgHIDmzJnDsGHDCo0Kd+3aBXBBD56A8WCbPx8OH4YLNVgBYI1OObB//3mDU6dONHXrRgclEnSNGjWYMWMGo0aN4tChQ9x4443UrFmTrKwsli9fTs+ePRk8eDDNmjVj7NixPP3002RnZ9O/f3/Cw8P57rvvSExMZNCgQYXq/vDDD5k9ezYDBw6kSZMmnDp1imeffZaYmBj3VIwvbdu25a677iItLY28vDy6du3KN998w5QpU7jrrrtK9BwqK3/5y1+YPXs2jz/+OBkZGTz++OMkJSXRo0cPRo8eTUJCAseOHWP9+vXs3LnTHcHgqaeeIjk5mauvvppx48bRoEEDdu7cyZo1a3juuedo3bo1jRs3JjU11e0xNGvWrKDJHRMTw7Rp03jggQe47bbbGDJkCDExMaxZs4bIyEgeeOABRIRBgwYxd+5cWrZsSatWrViyZEmpPP2GDRvGm2++yaRJk+jWrZu7U3Tx9NNP06NHD3r37s3IkSOpW7cuhw8fJjMzk/z8/GI7TdeDx3fffedldPr06cMHH3zA2LFjufnmm1m9ejXPPfdcQKMPMA8sd911F7fffjt/+tOfSEpKIiwsjN27d/PRRx/x5JNP0rJlS/r06cMzzzzD8OHDGTFiBFu3bmXKlCleXlzFEax79A9/+APPP/88AwYM4IknnkBEmDBhAg0bNvR64XPPnj00a9aMiRMnMnHiRMDcj1u2bOHaa6+lXr167Nmzh6eeeooDBw4UetB59NFHueKKK4iPj2f79u3MmDGDKlWqeLn7u/j222+pX79+oe+7RDzD4ZTHg2OwPBLK6yjSe60Ux4YNG0r04igtnl5mubl5unXrYT116lyhfC5vnW3bthVZl8tzac6cOX7PL1myRHv27KkxMTEaFRWlzZs31xEjRqjv9b300kvarl07rVq1qsbFxWlycrJ+/fXXXm24vKM2b96sd955pyYkJGi1atU0Pj5eb7zxRi/vMH+eWTk5OZqamqqNGjXSiIgIbdSokaampuq5c+evvajr8eeJ5Q+X95o/Hn30UQU0MzNTVVV//PFHHTlypNarV0+rVKmiderU0V69eml6erpXuczMTL355pu1Zs2aGhkZqa1atdLp06e7z//www/arVs3jYqK0vr16+uECRN0zpw5ha6/NN5rLt59911NSkrSyMhIjYmJ0aSkJM3IyHCfP3bsmA4dOlRr166tcXFxeu+99+qHH37o13utW7duRbaTl5enderUUUBfeeUVv3k2btyogwYN0ksuuUSrVq2q9evX1379+umSJUtKvI6kpCQdPny4V1p+fr6mpqZq3bp1NSoqSnv06KGZmZlF6svf7yE/P1+feeYZbd++vVarVk1r1Kih7du314cffliPHz/uzvfss89qQkKCRkZG6pVXXqmffvqpJicnF/KWLG/27Nmjt956q8bExGh0dLQOGDCg0H3g+i14enwuXrxYu3btqrVr19aIiAitVauW9uvXT7/99ttCbYwYMULr16+vVapU0fr16+vo0aP1yJEjfuVp3ry5jhs3LiDZvTzisrKMB9uzz7qTCKL3mmgAi2gVydq1a3d36NDhcDDq2lgO3msFBcr//d/PHDt2lsTEeMLCghcfzWKpDMyfP58HH3yQ/fv3F+sRaAkd3377rfvdJs9QOkWxadMmWrdubT6ommm122+HV14BQES+V9WghJywEQnKQHZ2Dhs3HiIrK5vTp3O9XKItll8LQ4cOpV69erz44osVLYrFYfr06aSkpARkcAohYtZ1yslt2hqdUpCbm8+uXcfYsuUIZ8/mERkZQcuWtYmLK3rx2mL5pRIREcG8efPsKOci4cyZM3Ts2JGpU6eWvpJ27cyaTjnMhFlHggvkyJHT7N17gvx8RQTq1o2hTp1oO61m+VXTpUuXCw4gaykfoqKimDRpUtkqadcOsrNh715o3Dg4gjlYo1MK8vOVGjWq0ahRTSIjrQotFssvDNcrEuvXB93oVIbptYKCgoIKG0bk5xdw8uR5P/5ataJo0aIWLVrUsgbHYrFUevw6k7mMTjms61z0RkdEDpw5cybAEKnB5fjxs2zYcIht28zajSMPNWtGBnUXT4vFYqkozpw5UziUUc2a0LBhuYTDueiNTl5e3uTdu3dXPXXqVFSoRjznzuWzfftRtm8/yrlz+URFVaGg4OJ2LbdYLJZAUVV3WKKffvrJHWLLi3btymWkc9HPD3Xq1OnjzMzM0Tt27JikqnUog6E8cuRIsSMUVSU7+xzHj581LzGJEBsbCVRlz56gvCpksVgsFwURERFERkbSqFEj//vttG0Ln34KHhsyBqXdoNZWTnTq1Olj4OOy1nPllVfq6tWrizw/evRHvPDCKgBuvbU1f/97Hxo0qFHWZi0Wi6Xy0a6dMTjbtgW12ot+ei2UjBlzFa1a1SYj4y4WLrzTGhyLxfLrpZycCUJudESkoYi8JyInROSkiCwSkUYBlo0UkRkisl9EzojINyLSozRyqCpvvfVvBg9e6PbeaNmyNhs3juLmm0vxFq/FYrH8kkhMNPvrBNmZIKRGR0SqA/8CEoEUYBjQAvhcRPzv1uTNXOAPwETgZmA/8LGIdCy2lA/bth2hd+8FDB68iLfeWs+SJeeHj/YlT4vFYgEiI6FFi6CPdEK9pvMHoCnQSlW3A4jIOmAbcC/wdFEFRaQDMBi4W1XnOWnLgQ3A40D/khpXVR5/fDl//esX5OTkU6tWFH/7Wy/69m1R1uuyWCyWXx7t2kFmZlCrDPX0Wn9gpcvgAKjqLuArYEAAZXOBf3qUzQPeBnqLSOE9c33YsOEQkyYtIycnn+HDO7J58yhGjuxkRzcWi8Xij7ZtYefOoFYZaqPTBvA3QbgBKGnPgTbALlU97adsVaD4vZ+BnJw8EhPjWbYshXnzBnDJJYHM6FksFsuvlHbtgh70M9TTa7WAY37SjwJxZSjrOl8IEfkj8EfnY87mzaPX9+w5OgBRf/HEA/blI4PVxXmsLs5jdXGeC9zzumgqxXs6ZUFVZwOzAURkdbA2IqrsWF2cx+riPFYX57G6OI+IFP2C4wUS6um1Y/gf0RQ1igm0LJwf8VgsFovlIiXURmcDZm3Gl8uAjQGUbeK4XfuWPQdsL1zEYrFYLBcToTY6i4EuItLUlSAiCUA351xxZABVgDs8ykYAg4BPVDWnqIIezL5AeX/JWF2cx+riPFYX57G6OE/QdCF+91IoJ5wXQNcCZ4DxgAJTgBigvar+7ORrDOwAHlfVxz3Kvw30Bh4GdgH3YV4S7aqqwXUmt1gsFkvQCelIR1VPAdcBW4F04A2M8bjOZXAcBAj3I98IYB7wBLAEaAj0sQbHYrFYKgchHelYLBaL5ddNpY8yfbEEEL0YKK0uRORKEZktIptF5LSI7BWRN0SkSSjkLg/Kcl/41PMXEVER+bI85AwFZdWFiLQWkXdF5LDzO9kiIg+Wp8zlRRn7i0Yi8prz+zgjIltF5IkA40ZeVIhIAxF5zunzTjv3eEKAZcNE5FER2S0iZ0VkrYjcFmjbldroXCwBRC8GyqiL/8B4FT4L3Aj8BegErBaRhuUmdDkRhPvCVU9TzNrjwfKQMxSUVRciciXwLVANuAfoC8zETH9XKsqiC+f8Z0APYAJGD/8AxgGvlqPY5UVz4E7MqyhfXGDZKUAa8Dymv1gJvCsifQMqraqV9gAeBPKB5h5pTYA84E8llO2AcWQY4ZEWAWwBFlf0tYVYF5f4SWsMFGCcOSr8+kKlC596PgZeAZYBX1b0dVXAfRGGeZXh/Yq+jotAFzc4/cUNPunTnfLVK/r6LlAXYR7/3+NcW0IA5S4FcoDJPun/C6wLpO1KPdKhggOIXmSUWheqeshP2h7gEFA/yHKGgrLcFwCIyGDMaO/RcpEwdJRFFz2B1hQT/b2SURZdVHX+nvRJP44xzpUqarCqFpSyaG+MLhb4pC8A2gUyJV/ZjU6FBhC9yCiLLgohIq0xTzWbyihXRVAmXYhIHDAL+C9VreyRLsqii2ucv5EislJEckXkoIg8KyJRQZUyNJRFF59htmB5UkQuE5FoEbkOM3p6WY1n7q+BNpiRju/L+BucvyX+viq70Ql5ANGLmLLowgvnpduXMSOduWUXLeSUVRczMG7984MoU0VRFl3Uc/7+E/gE+B3wN8x0zJvBEjCElFoXqnoWY4TDMB1sNmZK6UPg1xRBuBZwXJ05NQ8C7jd/8QE/LaXieaArcJOqlhQT7xeFiHQHfg908vPD+rXheihdoKoTnf+XiUg4MF1EWqtqZRwJXzAiEokxvpdiHBD2AkkYJ6Q8zIvqlgCo7EanrAFEGxdRFipfANGy6MKNiEzHbAWRoqqfBEm2UFMWXbyCGd39JCKxTloEEO58PqOBhVy6WCiLLo44fz/1Sf8Es4B+OZVr+rUsuhiJWeNqrqo7nLQVInICmC0iL6vq2qBJevFyDIgVEfF5KAu436zs02s2gOh5yqILAEQkFXgEGKOq6UGULdSURRetgf/E/LhcRzegi/N/ZXuiLetvpDhKuxhdUZRFF+2AYx4Gx8V3zt/WZZStsrAB4z7fzCfdtZZTYl9T2Y1ORQcQvZgoiy4QkTGY8EKpqvp8OckYKsqii2v9HGsxC9DXAu8FX9xypSy6+B/MonFvn/Q+zt+g7bESIsqiiwNAnIj4Ohhd5fzNCpKMFztLMV6/Q3zShwLrHW/A4qlof/Ey+pr/BjMi+TfG5bE/poPYCUR75GuMmXed6FP+bczT6z3A9ZgO5SxmPr/Cry9UusC8HFqA6WS6+ByXVfS1hfq+8FPfMirvezpl/Y1MctL/CvTCvDh8Bphf0dcWSl0ACRh36a2YF0uvxQQePokxvmGhvp4g6ON253gJ857Ofc7nZI88ecBcn3LTnX7yT5gpx5ec/uPmgNqt6AsPguIaAQudLz8b+ACfl5ycG0aBNJ/0KMw7CAccJX4L9Kzoawq1LjBeWlrEsayiryvU94Wfuiqt0SmrLjDvn/zJ6azPAXuAx4EqFX1dFaCLy4B3gB8xhncr8BQQV9HXVUpdlPibdz7P9ykXjonUsQczEl4H3B5ouzbgp8VisVhCRmVf07FYLBZLJcIaHYvFYrGEDGt0LBaLxRIyrNGxWCwWS8iwRsdisVgsIcMaHYvFYrGEDGt0LOWOiAx3tsP1d/S6gHp2i8j8chTVtz1POfNEZJeIzBORBkFuJ8FpY7hH2nARudtPXpcuE4IpQwny9fSji70i8qKzDURp6nxIRG4NtqyWi5/KHvDTUrm4A/jJJy2guHAVyHxMENAIoCMwGegqIh1V9UyQ2tgPXA14xvUa7rTpuxXyEifv/iC1fSGMAVYB1TERPB4BGgL9SlHXQ8CXwKKgSWepFFijYwkla9Rj18ZKQpaqrnT+/1JEsjGG6EaC1GGqifO3ssSMuHd5LbTTa4jY5KGLf4nIpcA9IlJHVQ9UkEyWSoadXrNUOCJyg4h8JCL7ReS0iKwXkXHOvi3FlasjIq+JyD4RyXHKf+h0hq481UXkSWdq7JzzN1VESnvvr3L+Nnfqrysir4vIYUeGdSIy9ELk9J1eE5FlQDLQzWNKa5lzzmtwZTf/AAAF7ElEQVR6TUSWiEimH93UdabBxnqkNRGRN0TkkCPHGhG5pZR6AHC128ijjc4i8p6I/CQiZ0Rki4j8VTx2GhWR3Zj4ZkM8rm++x/kOIrJYRI45dXwlZp8jyy8AO9KxhJJwJ5K3C1XVfKApZhfG5zAx8K4E0oBLMAEmiyId03k9jImH9VvMtE91cEcN/xgTM2sKJtBjF2ACZv+PcaW4Btce8MdF5DfAcsweLY85MgwF0kWkuqrODkROP9yP2XM+HLjXSTtZRN504C0RuUxVPacqBzt/3wQQkYaY2IIHgbGY0dIgYKGIDFTVEiOR+yEByAd2e6Q1AtZgRoPZmK0EJmK+4/9w8twCfIQJtpnmpB1y5OwEfAH8APwBOI3ZauIzEemqqt+XQk7LxURFB52zxy//wKxP+AssWCiIJibAZASQiokAHuZxbjcewQeBnzF7/xTV7jCnnR4+6amY4JWXliC3AlMdeSIxBmsTcAqzlfNoJ09Pn3KfYTr38ADlTHDqGe6RtqwI/bh0meB8jgJOANN88q0BPvL4PBfTsdf2yfcpZtqzOD30dNq8wdFFDDAQYwifKqac67sciolCXNvj3G7MjqS+Zf7X0XFVj7RwJ+2Dir6X7VH2w06vWULJLUBnj2MkuKeCXhGRPRhjkIvZ2ycWsz1wUawCHhaRB0WknYiIz/k+mEi4X4tIhOvA7HxZBWNESuIxR54zwDfO/31VdR/QA7Pms8ynzALMKM21sVVJcpYaNc4M72GmqgRARNoBHTCjIBd9MKOLEz66+BjoICI1AmjuY8z1nwTeB1ZgRm9uRKSGM525AxOBONeRQ4AWxVXuTMElA+8CBR4yCsaQ9whARstFjjU6llCyXlVXexxbnLWVxcDNGENzHcYgTXXKRBZT3yCn7H9hwqtnichEj/WaSzHTWrk+h2u3x9oByPyqI8/lQLyqtlfV5c65Wvj3IjvgcT4QOctKOsaLrKfzeRjnw/a7uBT4PYV1McM5H4guRmF00Qv4J3ATZqrSk3mY6bBngd85+Uc554r7LsHoK9yp01fO0ZhN1GyfVcmxazqWiqYZZg1nmKoucCWKSIluuKp6ENOhjRKRVpjNtSZjppFeAo4Au4A7i6hidwDy7VfVonbIPAq08pNex+N8IHKWleXAXmCoiCzHrOe8p94u3UcwayVPFlHHvgDa2erShYj8C7M29aiIzFPVH0UkErM5Wpqq/t1VyBl5BcJxzDTcC8Dr/jKoamXbItvigzU6lorGtZie60oQkSoU3g63WFR1C/CYiPwn0NZJXgrcBvysqpuDIKsvy4E7RKSbqn7lkT4Ys6ZT6B2kIuT0Rw5m7aREVFVFZAFmNPA+UB/vqTUwurga2KBBeL/IaXMsxoPtLxijWg0zUsn1yT7cTxU5mPUozzpPicgXmKnBTGtgfplYo2OpaDZh1l2mikg+psMaW3wREJGamHn+N4DNTrkBGE+yT5xsbwAjgP8VkZkYb6mqmNFVf2Cgqp4ug+zzgQeBRSKSinnxdQhmWuleVc0PUE5/bATuF5FBmJdGsx2DVRTpmPWnlzGjnmU+5ydiphVXiMjzmFFeHMbwNVXVQtEPSkJV14jIQmCkiExV1X0ishIYJyL7gcPA3Rgj6O/6uovIzZjpyMOquhuzS+kK4GMRmYuZvowHOmEcM4rzZrRUBirak8Eev/yD8x5XzYs43xHzdvppTMf9OHAPHl5aTr7dON5rmKfqV4ANGO+wk5gF+8E+dUdi3HI3Y56ujzr50oCIEuRW4IkS8tTFdPiHOb9171CP8yXKiX/vtTqYhf9sPLYQxsd7zUeWVc65vxYhawPgH0AWxmFjP8Z7bWgJ19jTqbeXn3OtMW7Tf/e4lv9x5D4IPI9Z+/Hy8gMSMdN9p/HZEtmp822nfI5zTyzGOHBU+P1sj7Iddrtqi8VisYQM6wlisVgslpBhjY7FYrFYQoY1OhaLxWIJGdboWCwWiyVkWKNjsVgslpBhjY7FYrFYQoY1OhaLxWIJGdboWCwWiyVk/D/hWrR///eacAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Best estimator: \", RF_best_model.best_estimator_)\n",
    "# X = X.values.reshape(-1, 1)\n",
    "RF_predict_train = RF_best_model.predict(X_train)\n",
    "RF_pre_prob_train = RF_best_model.predict_proba(X_train)\n",
    "model_evaluaiton(RF_predict_train, y_train, \"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## XGBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# xg_hyperparameters = {\n",
    "#                 'max_depth': [3, 4, 5],\n",
    "#                 'n_estimators': [50, 100],\n",
    "#                 'learning_rate': [0.1, 0.01, 0.05]\n",
    "#             }\n",
    "\n",
    "# best params => when PCA is used\n",
    "# xg_hyperparameters = {\n",
    "#                 'max_depth': [5],\n",
    "#                 'n_estimators': [100],\n",
    "#                 'learning_rate': [0.1]\n",
    "#             }\n",
    "\n",
    "### best params \n",
    "xg_hyperparameters = {\n",
    "                'max_depth': [5],\n",
    "                'n_estimators': [100],\n",
    "                'learning_rate': [0.03]\n",
    "            }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "xg_clf = GridSearchCV(estimator=xgb.XGBClassifier(random_state=RANDOM_STATE),\n",
    "                                   param_grid=xg_hyperparameters, cv=5,\n",
    "                                   scoring=scoring_fn, n_jobs=-1,verbose=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 5 folds for each of 1 candidates, totalling 5 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 12 concurrent workers.\n",
      "[Parallel(n_jobs=-1)]: Done   3 out of   5 | elapsed:  1.4min remaining:   54.2s\n",
      "[Parallel(n_jobs=-1)]: Done   5 out of   5 | elapsed:  1.4min finished\n"
     ]
    }
   ],
   "source": [
    "xgbb = xg_clf.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluating on Testing-set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best estimator:  XGBClassifier(base_score=0.5, booster=None, colsample_bylevel=1,\n",
      "              colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,\n",
      "              importance_type='gain', interaction_constraints=None,\n",
      "              learning_rate=0.03, max_delta_step=0, max_depth=5,\n",
      "              min_child_weight=1, missing=nan, monotone_constraints=None,\n",
      "              n_estimators=100, n_jobs=0, num_parallel_tree=1,\n",
      "              objective='binary:logistic', random_state=42, reg_alpha=0,\n",
      "              reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method=None,\n",
      "              validate_parameters=False, verbosity=None)\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.99      1.00      1.00     15625\n",
      "           1       0.93      0.66      0.77       375\n",
      "\n",
      "    accuracy                           0.99     16000\n",
      "   macro avg       0.96      0.83      0.88     16000\n",
      "weighted avg       0.99      0.99      0.99     16000\n",
      "\n",
      "[[15607    18]\n",
      " [  129   246]]\n",
      "Accuracy: 0.9908125\n",
      "roc_auc_score: 0.8274239999999999\n",
      "precision_score: 0.9318181818181818\n",
      "recall_score: 0.656\n",
      "f1_score: 0.7699530516431925\n",
      "CM: FP 18\n",
      "CM: FN 129\n",
      "APS Cost =  64680\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Best estimator: \", xgbb.best_estimator_)\n",
    "# X = X.values.reshape(-1, 1)\n",
    "xgbb_predict_test = xgbb.predict(X_test)\n",
    "xgbb_pre_prob_test = xgbb.predict_proba(X_test)\n",
    "model_evaluaiton(y_test, xgbb_predict_test, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Finding the threshold and then evaluate**\n",
    "- y_predict_prob_1 : classifier probability's output for minority class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1291/1291 [00:47<00:00, 27.17it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best threshold: 0.0568\n",
      "Min cost: 9810.00\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "xgbb_y_predict_prob_1 = xgbb_pre_prob_test[:,1]\n",
    "xgbb_best_th = find_cut_off(y_test, xgbb_y_predict_prob_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.97      0.98     15625\n",
      "           1       0.43      0.97      0.60       375\n",
      "\n",
      "    accuracy                           0.97     16000\n",
      "   macro avg       0.72      0.97      0.79     16000\n",
      "weighted avg       0.99      0.97      0.97     16000\n",
      "\n",
      "[[15144   481]\n",
      " [   10   365]]\n",
      "Accuracy: 0.9693125\n",
      "roc_auc_score: 0.9712746666666666\n",
      "precision_score: 0.4314420803782506\n",
      "recall_score: 0.9733333333333334\n",
      "f1_score: 0.5978705978705979\n",
      "CM: FP 481\n",
      "CM: FN 10\n",
      "APS Cost =  9810\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xgbb_predict_test_th = xgbb_pre_prob_test[:,1] > xgbb_best_th\n",
    "\n",
    "model_evaluaiton(y_test, xgbb_predict_test_th, \"\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Just example to prove the point of how the threshold works**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9432493187487125"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "0.943"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1.0-xgbb_best_th)\n",
    "xg_th = round((1.0-xgbb_best_th),3)\n",
    "xg_th"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9432493187487125"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.97      0.98     15625\n",
      "           1       0.43      0.97      0.60       375\n",
      "\n",
      "    accuracy                           0.97     16000\n",
      "   macro avg       0.72      0.97      0.79     16000\n",
      "weighted avg       0.99      0.97      0.97     16000\n",
      "\n",
      "[[15144   481]\n",
      " [   10   365]]\n",
      "Accuracy: 0.9693125\n",
      "roc_auc_score: 0.9712746666666666\n",
      "precision_score: 0.4314420803782506\n",
      "recall_score: 0.9733333333333334\n",
      "f1_score: 0.5978705978705979\n",
      "CM: FP 481\n",
      "CM: FN 10\n",
      "APS Cost =  9810\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# xgbb_predict_test_th = xgbb_pre_prob_test[:,1] >= xgbb_best_th\n",
    "# xgbb_predict_test_th = xgbb_pre_prob_test[:,0] < (1 - xgbb_best_th)\n",
    "\n",
    "xgbb_predict_test_th = xgbb_pre_prob_test[:,0] < xg_th\n",
    "\n",
    "(1 - xgbb_best_th)\n",
    "model_evaluaiton(y_test, xgbb_predict_test_th, \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evaluating on Training-set**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00     59000\n",
      "           1       0.96      0.76      0.85      1000\n",
      "\n",
      "    accuracy                           1.00     60000\n",
      "   macro avg       0.98      0.88      0.92     60000\n",
      "weighted avg       1.00      1.00      1.00     60000\n",
      "\n",
      "[[58972    28]\n",
      " [  239   761]]\n",
      "Accuracy: 0.99555\n",
      "roc_auc_score: 0.8802627118644069\n",
      "precision_score: 0.9645120405576679\n",
      "recall_score: 0.761\n",
      "f1_score: 0.8507546115148127\n",
      "CM: FP 28\n",
      "CM: FN 239\n",
      "APS Cost =  119780\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xgbb_predict_train = xgbb.predict(X_train)\n",
    "xgbb_pre_prob_train = xgbb.predict_proba(X_train)\n",
    "model_evaluaiton(y_train, xgbb_predict_train ,\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}