Online_fraud_detection_model.ipynb

{
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    "execution": {
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     "exception": false,
     "start_time": "2024-01-23T14:35:20.131793",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: xgboost in /opt/conda/lib/python3.10/site-packages (2.0.3)\r\n",
      "Requirement already satisfied: numpy in /opt/conda/lib/python3.10/site-packages (from xgboost) (1.24.3)\r\n",
      "Requirement already satisfied: scipy in /opt/conda/lib/python3.10/site-packages (from xgboost) (1.11.4)\r\n"
     ]
    }
   ],
   "source": [
    "# Install required libraries\n",
    "!pip install xgboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d4eceeda",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import xgboost as xgb\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix, roc_curve, auc\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import classification_report, roc_curve, auc, ConfusionMatrixDisplay\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "165b74be",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:35:38.852746Z",
     "iopub.status.busy": "2024-01-23T14:35:38.851336Z",
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    },
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     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('/kaggle/input/online-payment-fraud-detection/onlinefraud.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b5e4dca8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:00.958346Z",
     "iopub.status.busy": "2024-01-23T14:36:00.957895Z",
     "iopub.status.idle": "2024-01-23T14:36:00.982022Z",
     "shell.execute_reply": "2024-01-23T14:36:00.980632Z"
    },
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    "outputId": "e269eae9-5906-4709-dbce-c6f3625341d8",
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     "duration": 0.036525,
     "end_time": "2024-01-23T14:36:00.984917",
     "exception": false,
     "start_time": "2024-01-23T14:36:00.948392",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(6362620, 11)\n",
      "   step      type    amount     nameOrig  oldbalanceOrg  newbalanceOrig  \\\n",
      "0     1   PAYMENT   9839.64  C1231006815       170136.0       160296.36   \n",
      "1     1   PAYMENT   1864.28  C1666544295        21249.0        19384.72   \n",
      "2     1  TRANSFER    181.00  C1305486145          181.0            0.00   \n",
      "3     1  CASH_OUT    181.00   C840083671          181.0            0.00   \n",
      "4     1   PAYMENT  11668.14  C2048537720        41554.0        29885.86   \n",
      "\n",
      "      nameDest  oldbalanceDest  newbalanceDest  isFraud  isFlaggedFraud  \n",
      "0  M1979787155             0.0             0.0        0               0  \n",
      "1  M2044282225             0.0             0.0        0               0  \n",
      "2   C553264065             0.0             0.0        1               0  \n",
      "3    C38997010         21182.0             0.0        1               0  \n",
      "4  M1230701703             0.0             0.0        0               0  \n"
     ]
    }
   ],
   "source": [
    "print(df.shape)\n",
    "print(df.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "dc2ed89a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:01.003777Z",
     "iopub.status.busy": "2024-01-23T14:36:01.003104Z",
     "iopub.status.idle": "2024-01-23T14:36:03.118082Z",
     "shell.execute_reply": "2024-01-23T14:36:03.116882Z"
    },
    "id": "jO-1FF2h43wy",
    "outputId": "0238af74-0b58-49ce-f075-2c528855bab6",
    "papermill": {
     "duration": 2.128587,
     "end_time": "2024-01-23T14:36:03.121553",
     "exception": false,
     "start_time": "2024-01-23T14:36:00.992966",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Missing Values:\n",
      " step              0\n",
      "type              0\n",
      "amount            0\n",
      "nameOrig          0\n",
      "oldbalanceOrg     0\n",
      "newbalanceOrig    0\n",
      "nameDest          0\n",
      "oldbalanceDest    0\n",
      "newbalanceDest    0\n",
      "isFraud           0\n",
      "isFlaggedFraud    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Check for missing values\n",
    "missing_values = df.isnull().sum()\n",
    "print(\"Missing Values:\\n\", missing_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "31a706d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:03.146725Z",
     "iopub.status.busy": "2024-01-23T14:36:03.145310Z",
     "iopub.status.idle": "2024-01-23T14:36:05.702525Z",
     "shell.execute_reply": "2024-01-23T14:36:05.701170Z"
    },
    "id": "fm0jpdxh436X",
    "papermill": {
     "duration": 2.571933,
     "end_time": "2024-01-23T14:36:05.705596",
     "exception": false,
     "start_time": "2024-01-23T14:36:03.133663",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df = df.dropna()  # Remove rows with missing values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0edf29c4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:05.723661Z",
     "iopub.status.busy": "2024-01-23T14:36:05.723190Z",
     "iopub.status.idle": "2024-01-23T14:36:07.850776Z",
     "shell.execute_reply": "2024-01-23T14:36:07.849612Z"
    },
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     "duration": 2.140219,
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     "exception": false,
     "start_time": "2024-01-23T14:36:05.713854",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a correlation matrix\n",
    "correlation_matrix = df.corr(numeric_only=True)  # To calculate correlation only for numeric columns\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
    "plt.title(\"Correlation Matrix\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "86e7b746",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:07.874624Z",
     "iopub.status.busy": "2024-01-23T14:36:07.874178Z",
     "iopub.status.idle": "2024-01-23T14:36:08.282720Z",
     "shell.execute_reply": "2024-01-23T14:36:08.281429Z"
    },
    "id": "TpQfcgrb8bno",
    "papermill": {
     "duration": 0.422345,
     "end_time": "2024-01-23T14:36:08.285739",
     "exception": false,
     "start_time": "2024-01-23T14:36:07.863394",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Feature selection and splitting\n",
    "X = df.drop(['isFraud'], axis=1)\n",
    "y = df['isFraud']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "51b3dc2e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:08.306586Z",
     "iopub.status.busy": "2024-01-23T14:36:08.305551Z",
     "iopub.status.idle": "2024-01-23T14:36:12.588628Z",
     "shell.execute_reply": "2024-01-23T14:36:12.587500Z"
    },
    "id": "kcf-cPWxAxia",
    "papermill": {
     "duration": 4.296405,
     "end_time": "2024-01-23T14:36:12.591335",
     "exception": false,
     "start_time": "2024-01-23T14:36:08.294930",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Split the data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5d8fa0be",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:12.612040Z",
     "iopub.status.busy": "2024-01-23T14:36:12.611615Z",
     "iopub.status.idle": "2024-01-23T14:36:13.066722Z",
     "shell.execute_reply": "2024-01-23T14:36:13.065730Z"
    },
    "id": "hQJPo-gQAxmA",
    "papermill": {
     "duration": 0.468735,
     "end_time": "2024-01-23T14:36:13.069569",
     "exception": false,
     "start_time": "2024-01-23T14:36:12.600834",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Exclude non-numeric columns from the training and testing data\n",
    "non_numeric_columns = ['nameOrig', 'nameDest', 'type']\n",
    "X_train = X_train.drop(columns=non_numeric_columns)\n",
    "X_test = X_test.drop(columns=non_numeric_columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1c95c45a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:13.091214Z",
     "iopub.status.busy": "2024-01-23T14:36:13.090768Z",
     "iopub.status.idle": "2024-01-23T14:36:13.095918Z",
     "shell.execute_reply": "2024-01-23T14:36:13.094705Z"
    },
    "id": "6ewMcYOwDIU4",
    "papermill": {
     "duration": 0.018771,
     "end_time": "2024-01-23T14:36:13.098646",
     "exception": false,
     "start_time": "2024-01-23T14:36:13.079875",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Create an XGBoost classifier\n",
    "model = xgb.XGBClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bc0f7c15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:13.119406Z",
     "iopub.status.busy": "2024-01-23T14:36:13.118986Z",
     "iopub.status.idle": "2024-01-23T14:36:41.904775Z",
     "shell.execute_reply": "2024-01-23T14:36:41.903594Z"
    },
    "id": "JbFSUHqjDIdn",
    "outputId": "903a3a67-2577-4fe5-c76d-0a07fd147227",
    "papermill": {
     "duration": 28.799228,
     "end_time": "2024-01-23T14:36:41.907321",
     "exception": false,
     "start_time": "2024-01-23T14:36:13.108093",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
       "              colsample_bylevel=None, colsample_bynode=None,\n",
       "              colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "              gamma=None, grow_policy=None, importance_type=None,\n",
       "              interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "              multi_strategy=None, n_estimators=None, n_jobs=None,\n",
       "              num_parallel_tree=None, random_state=None, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBClassifier</label><div class=\"sk-toggleable__content\"><pre>XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
       "              colsample_bylevel=None, colsample_bynode=None,\n",
       "              colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "              gamma=None, grow_policy=None, importance_type=None,\n",
       "              interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "              multi_strategy=None, n_estimators=None, n_jobs=None,\n",
       "              num_parallel_tree=None, random_state=None, ...)</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
       "              colsample_bylevel=None, colsample_bynode=None,\n",
       "              colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "              enable_categorical=False, eval_metric=None, feature_types=None,\n",
       "              gamma=None, grow_policy=None, importance_type=None,\n",
       "              interaction_constraints=None, learning_rate=None, max_bin=None,\n",
       "              max_cat_threshold=None, max_cat_to_onehot=None,\n",
       "              max_delta_step=None, max_depth=None, max_leaves=None,\n",
       "              min_child_weight=None, missing=nan, monotone_constraints=None,\n",
       "              multi_strategy=None, n_estimators=None, n_jobs=None,\n",
       "              num_parallel_tree=None, random_state=None, ...)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the model on the training data\n",
    "model.fit(X_train, y_train)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b7991bcf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:41.929444Z",
     "iopub.status.busy": "2024-01-23T14:36:41.928645Z",
     "iopub.status.idle": "2024-01-23T14:36:44.503924Z",
     "shell.execute_reply": "2024-01-23T14:36:44.502683Z"
    },
    "id": "zS8j4PDBDIme",
    "papermill": {
     "duration": 2.589581,
     "end_time": "2024-01-23T14:36:44.506865",
     "exception": false,
     "start_time": "2024-01-23T14:36:41.917284",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Make predictions on the test set\n",
    "y_pred = model.predict(X_test)\n",
    "y_pred_prob = model.predict_proba(X_test)[:, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "78d657e0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:44.528970Z",
     "iopub.status.busy": "2024-01-23T14:36:44.528504Z",
     "iopub.status.idle": "2024-01-23T14:36:44.645001Z",
     "shell.execute_reply": "2024-01-23T14:36:44.643393Z"
    },
    "id": "D2EREM7MD6Nx",
    "outputId": "345ad2df-ee61-41b0-f0bc-71a98579bd92",
    "papermill": {
     "duration": 0.130218,
     "end_time": "2024-01-23T14:36:44.647690",
     "exception": false,
     "start_time": "2024-01-23T14:36:44.517472",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.9996605172083198\n"
     ]
    }
   ],
   "source": [
    "# Calculate accuracy\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(\"Accuracy:\", accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7da4d0a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:44.671074Z",
     "iopub.status.busy": "2024-01-23T14:36:44.670624Z",
     "iopub.status.idle": "2024-01-23T14:36:46.790579Z",
     "shell.execute_reply": "2024-01-23T14:36:46.789162Z"
    },
    "id": "QoK79EFYD6Vz",
    "outputId": "79564481-6d98-484d-ceff-94746c6b3cc4",
    "papermill": {
     "duration": 2.134797,
     "end_time": "2024-01-23T14:36:46.793267",
     "exception": false,
     "start_time": "2024-01-23T14:36:44.658470",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classification Report:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00   1270904\n",
      "           1       0.93      0.79      0.86      1620\n",
      "\n",
      "    accuracy                           1.00   1272524\n",
      "   macro avg       0.97      0.89      0.93   1272524\n",
      "weighted avg       1.00      1.00      1.00   1272524\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Generate classification report\n",
    "report = classification_report(y_test, y_pred)\n",
    "print(\"Classification Report:\\n\", report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a9c639de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:46.815020Z",
     "iopub.status.busy": "2024-01-23T14:36:46.814605Z",
     "iopub.status.idle": "2024-01-23T14:36:47.380762Z",
     "shell.execute_reply": "2024-01-23T14:36:47.379625Z"
    },
    "id": "yxuADtcLD6cy",
    "outputId": "543b6f59-2694-4240-afb1-b5779ba0038f",
    "papermill": {
     "duration": 0.580266,
     "end_time": "2024-01-23T14:36:47.383514",
     "exception": false,
     "start_time": "2024-01-23T14:36:46.803248",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Confusion Matrix')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a confusion matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "# Plot the confusion matrix\n",
    "ConfusionMatrixDisplay(cm).plot()\n",
    "plt.title('Confusion Matrix')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "aa7a199c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:47.408531Z",
     "iopub.status.busy": "2024-01-23T14:36:47.407357Z",
     "iopub.status.idle": "2024-01-23T14:36:48.055006Z",
     "shell.execute_reply": "2024-01-23T14:36:48.053604Z"
    },
    "id": "NdQwHzRDD6j3",
    "outputId": "70a4aae6-82c4-4968-fadf-850f8c768007",
    "papermill": {
     "duration": 0.662787,
     "end_time": "2024-01-23T14:36:48.057820",
     "exception": false,
     "start_time": "2024-01-23T14:36:47.395033",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5MktISAAA1TVhatSooTZfuXLl8j1k819mZmYA/n0NCyNXzjrPnj2LuXPnIjQ0FC9fvlSbPzExEebm5qrH+b0fCrKOu3fvAgAaNGig0XPIoenno6Dv3WXLlsHPzw/29vZwdXVFt27dMGjQIDg5OWmcMafwfdfnCCDfy0w4ODhg8+bNUCqVuHv3LhYuXIi4uLhcRaWpqelbi5PXP4tmZmaq7JpmfVuB967v3YLKaz+XK1cOffr0wa5du5CRkQF9fX0EBQUhKytLrRB6n7+5pI6FUBnVvHlzNG3aFMCrXos2bdrAx8cHERERMDExUV2/Y8qUKXn+SgZyf/G9iVKpRMOGDbFy5co8p9vb279xeW9vbyxcuBDx8fEwNTVFcHAwPvnkE1UPRE7egQMH5hpLlMPZ2VntcUF6g4BXY2h++uknXL16Fe3atctznqtXrwJAgX6l/9e7vM555R43bhy2bt2KCRMmoFWrVjA3N4dMJkP//v3zvRZLQb3e+5Qjvy81TdWpUwcAcO3aNTRu3LjAy70t1927d9GpUyfUqVMHK1euhL29PfT09HDkyBGsWrUq1+uS1+uq6Trelaafj4K+d/v164e2bdviwIED+OWXX7B8+XIsXboUQUFB+OCDD947d0FVqFABwL/F8+uMjY3Vxta1bt0aLi4umDlzJtauXatqr1u3LsLDw3H//v1chXCO1z+LderUweXLlxETE/PWvzP/lZCQkOcPmf/S9L2bX2GlUCjybM9vP/fv3x8bN27E0aNH4eXlhT179qBOnTpo1KiRap73/ZtL/2IhpAXkcjkWL16MDh064JtvvsH06dNVvxh1dXXV/kDlpXr16rh+/fpb57ly5Qo6depUoEMFr/P29sb8+fOxf/9+VKpUCUlJSapBgQBQsWJFmJqaQqFQvDWvpj788EMsXrwY27dvz7MQUigU2LVrFywtLdG6dWu1aX///Xeu+SMjI1U9JZq8zm+yb98++Pn5YcWKFaq29PR0vHjxQm2+d3nt3ybn4nh37txBhw4dVO3Z2dmIjo7OVYC+7oMPPoBcLscPP/xQqINOf/75Z2RkZCA4OFjtS1OTQwIFXUf16tUBANevX3/jD4T8Xv/3/Xy8ia2tLUaPHo3Ro0fj6dOncHFxwcKFC1WFUEG3l/NefdtnPS85BcO9e/cKNL+zszMGDhyIjRs3YsqUKarX/sMPP8SPP/6I7du3Y/bs2bmWS0pKwsGDB1GnTh3VfujRowd+/PFH/PDDD5gxY0aBtp+dnY2YmBj07NnzjfNp+t61tLTM9ZkEoPGVttu1awdbW1sEBgaiTZs2+O233zBr1iy1eYryPaVtOEZIS7Rv3x7NmzfH6tWrkZ6eDmtra7Rv3x4bN27E48ePc80fFxen+v8+ffrgypUrOHDgQK75cn6d9+vXDw8fPsTmzZtzzZOWlqY6+yk/devWRcOGDREYGIjAwEDY2tqqFSVyuRx9+vTB/v378/xD/d+8mnJzc4OHhwe2bt2a55VrZ82ahcjISHzxxRe5fsH99NNPamN8Lly4gPPnz6u+hDR5nd9ELpfn6qH5+uuvc/3SNDY2BoA8/xi/q6ZNm6JChQrYvHkzsrOzVe07d+7Mtwfgv+zt7TF8+HD88ssv+Prrr3NNVyqVWLFiBR48eKBRrpweo9cPE27durXQ19GlSxeYmppi8eLFSE9PV5v232WNjY3zPFT5vp+PvCgUilzbsra2RuXKlZGRkfHWTK+rWLEi2rVrhy1btuD+/ftq097WO2hnZwd7e3uNrrL8xRdfICsrS61H4+OPP0a9evWwZMmSXOtSKpUYNWoUEhISMHfuXLVlGjZsiIULFyI0NDTXdpKTk3MVETdv3kR6ejrc3NzemFHT92716tWRmJio6rUCgMePH+f5t/NNdHR08PHHH+Pnn3/Gjh07kJ2drXZYDCia95S2Yo+QFpk6dSr69u2LgIAAjBw5EuvWrUObNm3QsGFDDB8+HE5OTnjy5AlCQ0Px4MED1SXop06din379qFv37749NNP4erqiufPnyM4OBgbNmxAo0aN4Ovriz179mDkyJE4efIkWrduDYVCgdu3b2PPnj0ICQlRHarLj7e3N/z9/WFgYIChQ4dCR0e9Tl+yZAlOnjyJFi1aYPjw4ahXrx6eP3+OS5cu4fjx43j+/Pk7vzbbt29Hp06d0KtXL/j4+KBt27bIyMhAUFAQTp06BW9vb0ydOjXXcjVq1ECbNm0watQoZGRkYPXq1ahQoQK++OIL1TwFfZ3f5MMPP8SOHTtgbm6OevXqITQ0FMePH1cdksjRuHFjyOVyLF26FImJidDX10fHjh1hbW39zq+Nnp4e5s2bh3HjxqFjx47o168foqOjERAQgOrVqxfo1+iKFStw9+5djB8/HkFBQfjwww9haWmJ+/fvY+/evbh9+7ZaD2BBdOnSBXp6eujRowdGjBiBlJQUbN68GdbW1nkWne+zDjMzM6xatQrDhg1Ds2bN4OPjA0tLS1y5cgUvX77Etm3bAACurq4IDAzEpEmT0KxZM5iYmKBHjx6F8vl4XXJyMqpUqYKPP/5YdVuJ48eP46+//lLrOcwvU17Wrl2LNm3awMXFBZ999hkcHR0RHR2Nw4cPIzw8/I15evXqhQMHDhRo7A3w6tBWt27d8N1332HOnDmoUKEC9PT0sG/fPnTq1Alt2rTBkCFD0LRpU7x48QK7du3CpUuXMHnyZLX3iq6uLoKCguDh4YF27dqhX79+aN26NXR1dXHjxg1Vb+5/T///9ddfYWRkhM6dO781pybv3f79+2PatGno3bs3xo8fj5cvX2L9+vWoVauWxic1eHt74+uvv8bcuXPRsGHDXJfBKIr3lNYq/hPVqCjld0FFIV5dubR69eqievXqqtOz7969KwYNGiRsbGyErq6usLOzEx9++KHYt2+f2rLPnj0TY8eOVV36vkqVKsLPz0/tVPbMzEyxdOlSUb9+faGvry8sLS2Fq6urmD9/vkhMTFTN9/rp8zn+/vtv1UXfzpw5k+fze/LkiRgzZoywt7cXurq6wsbGRnTq1Els2rRJNU/OaeF79+7V6LVLTk4W8+bNE/Xr1xeGhobC1NRUtG7dWgQEBOQ6ffi/F1RcsWKFsLe3F/r6+qJt27biypUrudZdkNf5TfsuISFBDBkyRFhZWQkTExPh6ekpbt++nedruXnzZuHk5CTkcnmBLqj4+uuU34X21q5dK6pVqyb09fVF8+bNxdmzZ4Wrq6vo2rVrAV7dV1fh/e6770Tbtm2Fubm50NXVFdWqVRNDhgxROz05vytL57w+/72IZHBwsHB2dhYGBgbCwcFBLF26VGzZsiXXfDkXVMxLQdeRM6+bm5swNDQUZmZmonnz5uLHH39UTU9JSRE+Pj7CwsIi1wUVC/r5wP9faC8v+M/p8xkZGWLq1KmiUaNGwtTUVBgbG4tGjRrluhhkfpny28/Xr18XvXv3FhYWFsLAwEDUrl1bzJkzJ888/3Xp0iUBINfp3PldUFEIIU6dOpXrkgBCCPH06VMxadIkUaNGDaGvry8sLCyEh4eH6pT5vCQkJAh/f3/RsGFDYWRkJAwMDESDBg3EjBkzxOPHj9XmbdGihRg4cOBbn1OOgr53hRDil19+EQ0aNBB6enqidu3a4ocffnjjBRXzo1Qqhb29vQAgFixYkOc8BX1P0ZvJhCgld5MkKkGio6Ph6OiI5cuXY8qUKVLHkYRSqUTFihXx0Ucf5dk9T9qnU6dOqFy5Mnbs2CF1lHyFh4fDxcUFly5d0mjwPpVdHCNERG+Vnp6ea5zI9u3b8fz5c7Rv316aUFTiLFq0CIGBgRoPDi5OS5Yswccff8wiiFQ4RoiI3urPP//ExIkT0bdvX1SoUAGXLl3C999/jwYNGqBv375Sx6MSokWLFsjMzJQ6xhvt3r1b6ghUwrAQIqK3cnBwgL29PdauXYvnz5+jfPnyGDRoEJYsWZLvPdyIiEoDjhEiIiIircUxQkRERKS1WAgRERGR1tK6MUJKpRKPHj2CqakpL0tORERUSgghkJycjMqVK+e64O770LpC6NGjR7wZHRERUSkVExODKlWqFNr6tK4QMjU1BfDqhTQzM5M4DRERERVEUlIS7O3tVd/jhUXrCqGcw2FmZmYshIiIiEqZwh7WwsHSREREpLVYCBEREZHWYiFEREREWouFEBEREWktFkJERESktVgIERERkdZiIURERERai4UQERERaS0WQkRERKS1WAgRERGR1pK0EPr999/Ro0cPVK5cGTKZDD/99NNblzl16hRcXFygr6+PGjVqICAgoMhzEhERUdkkaSGUmpqKRo0aYd26dQWa/969e+jevTs6dOiA8PBwTJgwAcOGDUNISEgRJyUiIqKySNKbrn7wwQf44IMPCjz/hg0b4OjoiBUrVgAA6tatizNnzmDVqlXw9PQsqphERERURpWqu8+HhobCw8NDrc3T0xMTJkwongBCAEJRNOt++RRIvFc06yYqCnFXgKxUQMahhlRE7p8AIAN0jaROQhJTKoEbEUXzt6ZUFUKxsbGoVKmSWlulSpWQlJSEtLQ0GBoa5lomIyMDGRkZqsdJSUn5b0CpAO78BGS/BJ6EAYqsf6elxQORe973KRAREZEGHieZYEigF07ftSmS9ZeqQuhdLF68GPPnz3/zTFGHgQMfFk8gIiIiKpCD12tj2N6eiE81BpBeJNsoVYWQjY0Nnjx5otb25MkTmJmZ5dkbBAAzZszApEmTVI+TkpJgb2//7wzHRwFXNmgWxNwRMLHTbJmCSHsGVOsM6OgW/rqJikJ6PFCtCyDXkzoJlVU6eoB1E0AmkzoJFbO4+DQMmLsHqanZAADrioZ4Glf42ylVhVCrVq1w5MgRtbZff/0VrVq1yncZfX196Ovr554gBLC+0quxOa8ztgFazgGU2UDlVupjIMrXAXSN3/UpEBERUQFUNAVWr/4Aw4f/DC+vOli50h1OTnMLfTuSFkIpKSm4c+eO6vG9e/cQHh6O8uXLo2rVqpgxYwYePnyI7du3AwBGjhyJb775Bl988QU+/fRT/Pbbb9izZw8OHz6s+cavb8ldBA26AlR0fp+nRERERO9AoVAiO1sJff1/S5OhQ5vA3t4MXbpUR3JycpFsV9LTPS5evIgmTZqgSZMmAIBJkyahSZMm8Pf3BwA8fvwY9+/fV83v6OiIw4cP49dff0WjRo2wYsUKfPfdd+926vypSeqPRzxkEURERCSBmJhEeHjswJQpv6i1y2QyeHrWgKwID43KhBCiyNZeAiUlJcHc3ByJCwAzg/9vHB4NmFWTMhYREZFW2rPnBkaMOIQXL14Nhj582AfdutXMNZ/q+zsxEWZmZoW2/VI1RqjIsAgiIiIqVklJGRg//ii2bbuiarO3N4OpafGefMFCyCtY6gRERERaJTQ0BgMHHkBUVIKqzdu7Ptav7w5Ly7zPAi8qLIScukudgIiISCtkZyuxcOHv+PLL36FQvBqZY2qqh3XrumHgQOciHQuUH+0uhPQteHsAIiKiYvDs2Uv06PEjQkMfqNrc3Ozxww+94ehoKVku7a4CrBpKnYCIiEgrWFgYoFy5V2WHXC7D/Pntcfr0YEmLIEDbC6GqnaROQEREpBXkch3s2NEbLi62OHPmU/j7u6sKIylp96Ex40pvn4eIiIg0dvp0NAwNddG8+b+3pKpWzQIXLw6XZCxQfqQvxaRk7ih1AiIiojIlM1OBGTOOo0OHbfjkk/1ITs5Qm16SiiBA2wshIiIiKjQREfFo1ep7LFlyFkIAUVEJWL/+otSx3ki7D40ZWkudgIiIqNQTQmDz5kuYMOEY0tJe3S1eV1cHCxd2xOTJbhKnezPtLoTKGbx9HiIiIspXXFwqhg//GQcPRqjaateugF27+sDFxVbCZAWj3YWQjnY/fSIiovcREnIHgwcfRGxsiqpt5EhXrFjhCSMjXQmTFZx2VwK6xlInICIiKpWePEmBl1cg0tNfHQqzsjLCli090aNHbYmTaUa7B0vrFO+N3YiIiMqKSpVMsGTJq+vxeXpWx7Vro0pdEQRoe4+QnIUQERFRQSiVAgqFErq6clXbuHEtUKWKGXr3rgsdnZJ1WnxBaXePEAshIiKit3r8OBkffLATs2f/ptauoyNDnz71Sm0RBGh7IaRTOgZyERERSeXgwdto2HA9fvnlLpYvP4fffrsndaRCpd2HxnTkb5+HiIhIC6WmZmLy5F+wcWOYqq1SJRMJExUN7S2EWAQRERHlKSzsEXx8ghAZ+UzV1qtXbXz3XU9YWRlJmKzwaXEhpL1PnYiIKC8KhRJffXUOs2efRHa2EgBgZKSL1as9MWyYS4m7T1hh0N5qQKa9T52IiOh18fEv0bfvXpw6Fa1qc3W1xa5dfVCrVgXpghUx7R0szUKIiIhIxdxcHykpmQAAmQyYMaMNzp0bWqaLIECrCyHtfepERESv09WVY+fOj1C3rhVOnvTDokWdoKdX9sfTam+3CMcIERGRFgsNjYGRkS4aNbJRtdWqVQHXr48u1dcF0pT2doukxUmdgIiIqNhlZysxf/4ptG27FZ98sh8vX2apTdemIgjQ5kKIiIhIy0RFJaBdu62YN+80FAqBW7fi8e23f0kdS1Lae3zItKrUCYiIiIqFEAI7dlzF2LFHkJz8akC0XC7D3LnumDChpcTppKW9hRAHSxMRkRZISEjDyJGHsWfPDVVb9eqW+OGHj9CyZRUJk5UMLISIiIjKqFOnouHrewAPHiSp2oYMaYw1a7rC1FRfwmQlhxYXQto1GIyIiLTL48fJ8PT8AZmZCgCApaUBNm78EH371pc4Wcmivd0i7BEiIqIyzNbWFHPnugMAOnRwwNWro1gE5UGLe4RYCBERUdkhhIBSKSCX//v9Nm1aa9jbm2HAAGetOy2+oLS3GmAhREREZURcXCp69w7EggW/q7XL5Trw9W3EIugN2CNERERUioWE3MHgwQcRG5uCQ4ci0aVLdbRqZS91rFJDewshLe4MIyKi0i89PRszZhzH6tXnVW2Wloaq6wRRwWhvIcQeISIiKqWuXXuCAQOCcO3aU1Wbp2d1BAR4wcbGRMJkpQ8LISIiolJCqRT4+uvzmDbtODIyXp0Wr68vx7JlnTF2bHOOBXoH2lsI8dAYERGVIs+evcSAAUEICbmramvY0Bq7dvVBgwbWEiYr3bS3Gsh4LnUCIiKiAjM21sPDh8mqxxMntsSFC8NZBL0n7S2EkqKlTkBERFRgBgblsGvXR3B0tEBIyECsXOkJAwMtPrBTSLT3FbRuKnUCIiKifIWFPYKxsR7q1LFStTVsWAmRkeNQrpz29mMUNr6SREREJYhCocTSpWfQsuX3+OST/cjIyFabziKocPHVJCIiKiFiYhLRqdN2TJ9+AtnZSoSHx+Lbb/+SOlaZpr2HxoiIiEqQPXtuYMSIQ3jxIh0AIJMB06e3wZgxzSVOVraxECIiIpJQUlIGxo8/im3brqja7O3NsGNHb7i7O0gXTEuwECIiIpJIaGgMBg48gKioBFWbt3d9rF/fHZaWhhIm0x4shIiIiCTw8GES2rffhszMV1eINjXVw7p13TBwoDNkMl4hurhwsDQREZEE7OzMMGVKKwCAm5s9rlwZCV/fRiyCihl7hIiIiIqBEAIA1AqdefPao2pVcwwd6sLT4iXCV52IiKiIJSSkoX///VixIlStXVdXjhEjmrIIkpD29gix65GIiIrBqVPR8PU9gAcPknDgwC106uSIJk1spY5F/48lKBERURHIzFRg+vTj6NhxGx48SAIAmJjoITY2ReJk9F/a2yNERERURCIi4uHjE4RLlx6r2jp0cMD27b1RpYqZhMnodSyEiIiICokQAps2hWHixBCkpb26R5iurg4WLuyIyZPdoKPDYRklDQshIiKiQvD8eRqGDDmI4OAIVVvt2hWwa1cfuLhwTFBJxUKIiIioEOjry3H7drzq8ahRTfHVV11gZKQrYSp6Gw6WJiIiKgTGxnrYufMjVK5siuDg/vj22+4sgkoB9ggRERG9g2vXnsDYWA9OTpaqtqZNKyMqajz09fn1WlqwR4iIiEgDSqXAmjV/olmzzRgwIAjZ2Uq16SyCShcWQkRERAX0+HEyPvhgJyZMCEFGhgJ//vkA69f/JXUseg+SF0Lr1q2Dg4MDDAwM0KJFC1y4cOGN869evRq1a9eGoaEh7O3tMXHiRKSnpxdTWiIi0lYHD95Gw4br8csvd1VtEye2xPDhrhKmovclaf9dYGAgJk2ahA0bNqBFixZYvXo1PD09ERERAWtr61zz79q1C9OnT8eWLVvg5uaGyMhIDB48GDKZDCtXrtRw67yWAxERvV1qaiYmT/4FGzeGqdpsbU0QEOCFLl2qS5iMCoOkPUIrV67E8OHDMWTIENSrVw8bNmyAkZERtmzZkuf8586dQ+vWreHj4wMHBwd06dIFn3zyyVt7kYiIiN5FWNgjuLhsUiuCvLzq4OrVUSyCygjJCqHMzEyEhYXBw8Pj3zA6OvDw8EBoaGiey7i5uSEsLExV+ERFReHIkSPo1q1bvtvJyMhAUlKS2j8iIqK3iYlJhJvbFkRGPgMAGBnpYvPmHggK6gcrKyOJ01FhkawQio+Ph0KhQKVKldTaK1WqhNjY2DyX8fHxwf/+9z+0adMGurq6qF69Otq3b4+ZM2fmu53FixfD3Nxc9c/e3r5QnwcREZVN9vbmGD26KQDA1dUWly+PwLBhLpDJOLSiLJF8sLQmTp06hUWLFuHbb7/FpUuXEBQUhMOHD+PLL7/Md5kZM2YgMTFR9S8mJqYYExMRUWkihFB7vHixB1au7IJz54aiVq0KEqWioiTZYGkrKyvI5XI8efJErf3JkyewsbHJc5k5c+bA19cXw4YNAwA0bNgQqamp+OyzzzBr1izo6OSu6/T19aGvr1/4T4CIiMqMpKQMjB9/FM2b22H06GaqdgODcpg4sZWEyaioSdYjpKenB1dXV5w4cULVplQqceLECbRqlfeb7uXLl7mKHblcDiB3FU9ERFQQoaExaNx4A7Ztu4LJk3/BrVtxUkeiYiTp6fOTJk2Cn58fmjZtiubNm2P16tVITU3FkCFDAACDBg2CnZ0dFi9eDADo0aMHVq5ciSZNmqBFixa4c+cO5syZgx49eqgKIiIiooLIzlZiwYLfsWDB71AoXv2Y1tXVwd27Cahbt6LE6ai4SFoIeXt7Iy4uDv7+/oiNjUXjxo1x7Ngx1QDq+/fvq/UAzZ49GzKZDLNnz8bDhw9RsWJF9OjRAwsXLpTqKRARUSkUFZWAgQODEBr6QNXm5maPH37oDUdHyzcsSWWNTGjZMaWkpCSYm5sj8bsWMBv6p9RxiIioGAkhsH37FYwdexQpKZkAALlcBn9/d8yc2RblypWqc4i0iur7OzERZmZmhbZe3hmOiIi0wosX6Rgx4hD27LmhanNyssTOnR+hZcsqEiYjKWlvIcTrQBARaRWZDDh//t9DYYMHN8batV1hasozi7UZ+wCJiEgrmJsbYMeO3rCyMsKePR9j69ZeLIJIi3uEiIioTIuIiIexsR6qVPl3PEnbttUQHf05jI31JExGJQl7hIiIqEwRQmDjxoto0mQjBg06AKVS/ZwgFkH0XyyEiIiozIiLS4WXVyBGjjyMtLRsnDwZjU2bwt6+IGktHhojIqIyISTkDgYPPojY2BRV28iRrhg0qJGEqaikYyFERESlWnp6NmbMOI7Vq8+r2qysjLBlS0/06FFbwmRUGrAQIiKiUuvatScYMCAI1649VbV5elZHQIAXbGxMJExGpQULISIiKpX++ecFmjXbjIwMBQBAX1+OZcs6Y+zY5tDR4bXiqGA4WJqIiEqlatUsVON/Gja0xsWLn2H8+BYsgkgj7BEiIqJSa9UqT1SrZo7Jk91gYMCvNNKcFvcI8RcDEVFpkZqaiZEjDyEgIFyt3dhYD7NmtWMRRO+M7xwiIirRwsIeYcCAIEREPMPOndfQtm1VVK9eXupYVEZocY8QERGVZAqFEkuXnkHLlt8jIuIZAECpFLh+/elbliQqOPYIERFRiRMTkwhf3wM4ffofVZurqy127eqDWrUqSJiMyhoWQkREVKLs2XMDI0YcwosX6QAAmQyYPr0N5s1rDz09ucTpqKxhIURERCVCcnIGxo07im3brqja7O3NsGNHb7i7O0gXjMo0FkJERFQiZGQo8Msvd1WPvb3rY/367rC0NJQwFZV1HCxNREQlgpWVEbZt84KZmT62b/fCjz/2YRFERY49QkREJImoqAQYG+uiUqV/7wnWuXN1/PPPBFhYGEiYjLQJe4SIiKhYCSGwbVs4GjXagE8/DYYQQm06iyAqTiyEiIio2CQkpKF///0YPPggUlIyceTI39i6NVzqWKTFtPfQmIy32CAiKk6nTkXD1/cAHjxIUrUNHtwYffvWkzAVaTvtLYSIiKhYZGYq4O9/EsuWnUXOUTBLSwNs3Pgh+vatL2040noshIiIqMjcvh2PAQOCcOnSY1Vbhw4O2L69N6pUMZMwGdErLISIiKhIREUlwMVlI9LSsgEAuro6WLiwIyZPdoOODocnUMnAwdJERFQknJws8dFHdQEAtWtXwJ9/DsPUqa1ZBFGJwh4hIiIqMuvWdUO1auaYNasdjIx0pY5DlMt79Qilp6cXVg4iIirF0tOzMXHiMezde0Ot3dzcAAsXdmIRRCWWxoWQUqnEl19+CTs7O5iYmCAqKgoAMGfOHHz//feFHpCIiEq2a9eeoHnzzVi9+jw+++wQYmISpY5EVGAaF0ILFixAQEAAli1bBj09PVV7gwYN8N133xVqOCIiKrmUSoE1a/5Es2abce3aUwBAWloWLl58JHEyooLTuBDavn07Nm3ahAEDBkAul6vaGzVqhNu3bxdqOCIiKpkeP05Gt247MWFCCDIyFACAhg2tcfHiZ+jdu67E6YgKTuPB0g8fPkSNGjVytSuVSmRlZRVKKCIiKrkOHryNYcN+Rnz8S1XbxIktsWhRJxgY8BwcKl00fsfWq1cPf/zxB6pVq6bWvm/fPjRp0qTQghU9nr5JRKSJ1NRMTJ78CzZuDFO12dqaICDAC126VJcwGdG707gQ8vf3h5+fHx4+fAilUomgoCBERERg+/btOHToUFFkJCKiEiApKQP7999SPfbyqoPNm3vAyspIwlRE70fjMUK9evXCzz//jOPHj8PY2Bj+/v64desWfv75Z3Tu3LkoMhIRUQlga2uK777rASMjXWze3ANBQf1YBFGpJxMi5xZ42iEpKQnm5uZI3NIaZkPOSB2HiKjEiolJhLGxHsqXN1Rrf/o0FdbWxhKlIm2l+v5OTISZWeHdp07jHiEnJyc8e/YsV/uLFy/g5ORUKKGIiEhae/bcgLPzBowYcQiv/15mEURlicaFUHR0NBQKRa72jIwMPHz4sFBCERGRNJKSMjB48E/w9t6HFy/SsW/fTezadU3qWERFpsCDpYODg1X/HxISAnNzc9VjhUKBEydOwMHBoVDDERFR8QkNjcGAAUG4d++Fqs3buz66daspXSiiIlbgQsjLywsAIJPJ4OfnpzZNV1cXDg4OWLFiRaGGIyKiopedrcTChb/jyy9/h0Lx6jCYqake1q3rhoEDnSGT8XIjVHYVuBBSKpUAAEdHR/z111+wsrIqslBERFQ8oqISMHBgEEJDH6ja3Nzs8cMPveHoaClhMqLiofF1hO7du1cUOYiIqJjdufMcLi4bkZycCQCQy2Xw93fHzJltUa6cxkNIiUqld7oWempqKk6fPo379+8jMzNTbdr48eMLJRgRERWt6tUt0amTE3766TacnCyxc+dHaNmyitSxiIqVxoXQ5cuX0a1bN7x8+RKpqakoX7484uPjYWRkBGtr69JTCPGYNxFpOZlMhs2be6BaNXN8+WUHmJrqSx2JqNhp3Pc5ceJE9OjRAwkJCTA0NMSff/6Jf/75B66urvjqq6+KIiMREb2nzEwFpk8/jsOHI9XarayMsHp1VxZBpLU0LoTCw8MxefJk6OjoQC6XIyMjA/b29li2bBlmzpxZFBmJiOg9RETEo1Wr77F06Vl8+mkwnjxJkToSUYmhcSGkq6sLHZ1Xi1lbW+P+/fsAAHNzc8TExBRuOiIiemdCCGzceBFNmmzEpUuPAQAJCWk4e5Z/q4lyaDxGqEmTJvjrr79Qs2ZNuLu7w9/fH/Hx8dixYwcaNGhQFBmJiEhDcXGpGDbsZwQHR6jaateugF27+sDFxVbCZEQli8Y9QosWLYKt7asP0cKFC2FpaYlRo0YhLi4OGzduLPSARESkmZCQO3B23qBWBI0a1RSXLo1gEUT0Go17hJo2bar6f2traxw7dqxQAxER0btJT8/GjBnHsXr1eVWblZURtmzpiR49akuYjKjkKrQrZl26dAkffvhhYa2OiIg09PRpKrZuDVc97tq1Bq5dG8UiiOgNNCqEQkJCMGXKFMycORNRUVEAgNu3b8PLywvNmjVT3YaDiIiKX9Wq5li/vjv09eVYu7YrjhzxgY2NidSxiEq0Ah8a+/777zF8+HCUL18eCQkJ+O6777By5UqMGzcO3t7euH79OurWrVuUWYmI6D8eP06GsbEezMz+vQbQJ580RJs2VWFvby5hMqLSo8A9QmvWrMHSpUsRHx+PPXv2ID4+Ht9++y2uXbuGDRs2sAgiIipGBw/ehrPzBowffzTXNBZBRAVX4ELo7t276Nu3LwDgo48+Qrly5bB8+XJUqVJa70vDW2wQUemTmpqJkSMPwcsrEPHxL7Ft2xXs339T6lhEpVaBD42lpaXByMgIwKv70+jr66tOoycioqIXFvYIPj5BiIx8pmrz8qoDd3cH6UIRlXIanT7/3XffwcTk1cC77OxsBAQEwMrKSm2eUnPTVSKiUkKhUOKrr85h9uyTyM5+dVKKkZEu1qzpiqFDm0DGm0gTvTOZEEIUZEYHB4e3fthkMpnqbLKCWrduHZYvX47Y2Fg0atQIX3/9NZo3b57v/C9evMCsWbMQFBSE58+fo1q1ali9ejW6detWoO0lJSXB3NwciVvbwmzw7xplJSIqbjExifD1PYDTp/9Rtbm62mLXrj6oVauChMmIipfq+zsxEWZmZoW23gL3CEVHRxfaRnMEBgZi0qRJ2LBhA1q0aIHVq1fD09MTERERsLa2zjV/ZmYmOnfuDGtra+zbtw92dnb4559/YGFhUejZiIikFhn5DC1afIcXL9IBADIZMH16G8yb1x56enKJ0xGVDRpfWbowrVy5EsOHD8eQIUMAABs2bMDhw4exZcsWTJ8+Pdf8W7ZswfPnz3Hu3Dno6uoCeNVTRURUFtWoUR4tWtghJOQu7O3NsGNHb44HIipkhXZlaU1lZmYiLCwMHh4e/4bR0YGHhwdCQ0PzXCY4OBitWrXCmDFjUKlSJTRo0ACLFi2CQqEorthERMVGR0eGrVt74bPPXHDlykgWQURFQLIeofj4eCgUClSqVEmtvVKlSrh9+3aey0RFReG3337DgAEDcOTIEdy5cwejR49GVlYW5s6dm+cyGRkZyMjIUD1OSkoqvCdBRFRIsrOVWLjwd7RtWw0dOzqq2m1tTbFxYw8JkxGVbZIeGtOUUqmEtbU1Nm3aBLlcDldXVzx8+BDLly/PtxBavHgx5s+fX8xJiYgKLioqAQMHBiE09AHs7Exx9eoolC9vKHUsIq0g2aExKysryOVyPHnyRK39yZMnsLGxyXMZW1tb1KpVC3L5v4ME69ati9jYWGRmZua5zIwZM5CYmKj6FxMTU3hPgojoPQghsH37FTRuvAGhoQ8AALGxKTh58p7EyYi0xzsVQnfv3sXs2bPxySef4OnTpwCAo0eP4saNGwVeh56eHlxdXXHixAlVm1KpxIkTJ9CqVas8l2ndujXu3LmjdnPXyMhI2NraQk9PL89l9PX1YWZmpvaPiEhqCQlp6N9/P/z8fkJy8qsfck5Oljhz5lP06VNP4nRE2kPjQuj06dNo2LAhzp8/j6CgIKSkpAAArly5ku/hqfxMmjQJmzdvxrZt23Dr1i2MGjUKqampqrPIBg0ahBkzZqjmHzVqFJ4/f47PP/8ckZGROHz4MBYtWoQxY8Zo+jRenYdKRCSBU6ei4ey8AXv2/PvjcfDgxggPH4GWLUvrbYuISieNxwhNnz4dCxYswKRJk2Bqaqpq79ixI7755huN1uXt7Y24uDj4+/sjNjYWjRs3xrFjx1QDqO/fvw8dnX9rNXt7e4SEhGDixIlwdnaGnZ0dPv/8c0ybNk3Tp0FEVOwyMxWYO/ckli49i5xL2VpYGGDTpg/Rt299acMRaakCX1k6h4mJCa5duwZHR0eYmpriypUrcHJyQnR0NOrUqYP09PSiylooVFemDGgHM7/TUschIi0SFZUAZ+f1SE3NAgC0b++A7du9eLd4ogIoqitLa3xozMLCAo8fP87VfvnyZdjZ2RVKKCKissjJyRJr1nSFrq4Oli3zwIkTg1gEEUlM40Nj/fv3x7Rp07B3717IZDIolUqcPXsWU6ZMwaBBg4oiIxFRqRQf/xJGRrowMtJVtX36aRO4uzugRo3yEiYjohwa9wgtWrQIderUgb29PVJSUlCvXj20a9cObm5umD17dlFkJCIqdUJC7qBhw/WYOvUXtXaZTMYiiKgE0XiMUI779+/j+vXrSElJQZMmTVCzZs3CzlYkOEaIiIpSeno2Zsw4jtWrz6vaDh36BN2715IwFVHpJ/nd53OcOXMGbdq0QdWqVVG1atVCC0JEVNpdu/YEAwYE4dq1p6q2rl1rwNW1soSpiOhNND401rFjRzg6OmLmzJm4efNmUWQiIipVlEqBNWv+RLNmm1VFkL6+HGvXdsWRIz6wsTGROCER5UfjQujRo0eYPHkyTp8+jQYNGqBx48ZYvnw5Hjx4UBT5iIhKtMePk9Gt205MmBCCjAwFAKBhQ2tcvPgZxo1rARkv3kpUomlcCFlZWWHs2LE4e/Ys7t69i759+2Lbtm1wcHBAx44diyIjEVGJFBERD2fnDQgJuatqmzixJS5cGI4GDawlTEZEBfVeN111dHTE9OnTsWTJEjRs2BCnT5emwcf8lUZE76dGjfKoV68iAMDW1gQhIQOxcqUnDAw0Hn5JRBJ550Lo7NmzGD16NGxtbeHj44MGDRrg8OHDhZmNiKhEk8t1sGNHb/j6OuPq1VHo0qW61JGISEMa/2yZMWMGdu/ejUePHqFz585Ys2YNevXqBSMjo6LIR0RUIigUSnz11Tm0bVsNbm72qvaqVc2xfXtvCZMR0fvQuBD6/fffMXXqVPTr1w9WVlZFkYmIqESJiUmEr+8BnD79DxwdLRAePhJmZvpSxyKiQqBxIXT27NmiyEFEVCLt2XMDI0YcwosXr24oHR39Ar/8chcff1xP4mREVBgKVAgFBwfjgw8+gK6uLoKDg984b8+ePQslGBGRlJKSMjB+/FFs23ZF1WZvb4YdO3rD3d1BumBEVKgKVAh5eXkhNjYW1tbW8PLyync+mUwGhUJRWNmIiCQRGhqDgQMPICoqQdXm7V0f69d3h6WloYTJiKiwFagQUiqVef4/EVFZkp2txMKFv+PLL3+HQvHqNoympnpYt64bBg505sURicogjU+f3759OzIyMnK1Z2ZmYvv27YUSiohICnfvPsfixWdURZCbmz2uXBkJX99GLIKIyiiNC6EhQ4YgMTExV3tycjKGDBlSKKGIiKRQu7YVli3rDLlchvnz2+P06cFwdLSUOhYRFSGNzxoTQuT5y+jBgwcwNzcvlFBERMUhISENRka60Nf/90/huHHN0bGjI2+RQaQlClwINWnSBDKZDDKZDJ06dUK5cv8uqlAocO/ePXTt2rVIQhYNdnMTabNTp6Lh63sA/fvXx/LlXVTtMpmMRRCRFilwIZRztlh4eDg8PT1hYmKimqanpwcHBwf06dOn0AMSERWmzEwF5s49iaVLz0II4KuvQtG1aw106uQkdTQikkCBC6G5c+cCABwcHODt7Q0DA4MiC0VEVBQiIuLh4xOES5ceq9o6dHBA7dq8Sj6RttJ4jJCfn19R5CAiKjJCCGzaFIaJE0OQlpYNANDV1cHChR0xebIbdHR4qJxIWxWoECpfvjwiIyNhZWUFS0vLN55G+vz580ILR0T0vuLiUjFs2M8IDo5QtdWuXQG7dvWBi4uthMmIqCQoUCG0atUqmJqaqv6f19MgotIgIiIe7dtvQ2xsiqpt1Kim+OqrLjAy0pUwGRGVFAUqhP57OGzw4MFFlYWIqFA5OVnC3t4MsbEpsLIywpYtPdGjR22pYxFRCaLxBRUvXbqEa9euqR4fPHgQXl5emDlzJjIzMws1HBHR+9DVlWPnzo/w0Ud1ce3aKBZBRJSLxoXQiBEjEBkZCQCIioqCt7c3jIyMsHfvXnzxxReFHpCIqCCUSoG1a8/j8uXHau01a1bA/v39YGNjks+SRKTNNC6EIiMj0bhxYwDA3r174e7ujl27diEgIAD79+8v7HxERG/1+HEyunXbic8/PwYfnyC8fJkldSQiKiU0LoSEEKo70B8/fhzdunUDANjb2yM+Pr5w0xERvcXBg7fh7LwBISF3AQC3b8fj6NG/JU5FRKWFxtcRatq0KRYsWAAPDw+cPn0a69evBwDcu3cPlSpVKvSARYZnvhGVaqmpmZg8+Rds3BimarO1NUFAgBe6dKkuYTIiKk00LoRWr16NAQMG4KeffsKsWbNQo0YNAMC+ffvg5uZW6AGJiF4XFvYIPj5BiIx8pmrz8qqDzZt7wMrKSMJkRFTaaFwIOTs7q501lmP58uWQy+WFEoqIKC8KhRLLl5/DnDknkZ396hC9kZEuVq/2xLBhLrzGGRFpTONCKEdYWBhu3boFAKhXrx5cXFwKLRQRUV5u345XK4JcXW2xa1cf1KpVQeJkRFRaaVwIPX36FN7e3jh9+jQsLCwAAC9evECHDh2we/duVKxYsbAzEhEBAOrXt8aXX3bAzJknMH16G8yb1x56euyJJqJ3p/FZY+PGjUNKSgpu3LiB58+f4/nz57h+/TqSkpIwfvz4oshIRFoqOTlD1fuTY+pUN1y4MByLFnViEURE703jQujYsWP49ttvUbduXVVbvXr1sG7dOhw9erRQwxGR9goNjUHjxhuxYMHvau1yuQ6aNq0sUSoiKms0LoSUSiV0dXPfrFBXV1d1fSEioneVna3E/Pmn0LbtVkRFJeDLL3/HuXMxUsciojJK40KoY8eO+Pzzz/Ho0SNV28OHDzFx4kR06tSpUMMRkXaJikpAu3ZbMW/eaSgUAgDQsmUV2Nry9hhEVDQ0LoS++eYbJCUlwcHBAdWrV0f16tXh6OiIpKQkfP3110WRkYjKOCEEtm+/gsaNNyA09AEAQC6XYf789jh9ejAcHS2lDUhEZZbGZ43Z29vj0qVLOHHihOr0+bp168LDw6PQwxFR2ZeQkIZRow4jMPCGqs3JyRI7d36Eli2rSJiMiLSBRoVQYGAggoODkZmZiU6dOmHcuHFFlasY8MJrRFKLiIhH5847EBOTpGobPLgx1q7tClNTfQmTEZG2KHAhtH79eowZMwY1a9aEoaEhgoKCcPfuXSxfvrwo8xFRGVatmgUsLAwQE5MES0sDbNz4Ifr2rS91LCLSIgUeI/TNN99g7ty5iIiIQHh4OLZt24Zvv/22KLMRURlnYFAOu3b1QbduNXH16igWQURU7ApcCEVFRcHPz0/12MfHB9nZ2Xj8+HGRBCOiskUIgU2bwnDzZpxae4MG1jh82AdVqphJlIyItFmBC6GMjAwYGxv/u6CODvT09JCWllYkwYio7IiLS4WXVyBGjDgEH5/9yMjIljoSEREADQdLz5kzB0ZGRqrHmZmZWLhwIczNzVVtK1euLLx0RFTqhYTcweDBBxEbmwIAuHLlCQ4dikSfPvUkTkZEpEEh1K5dO0RERKi1ubm5ISoqSvVYJuOZWET0Snp6NqZPP441a86r2qysjLBlS0/06FFbwmRERP8qcCF06tSpIoxBRGXJtWtP4OMThOvXn6raPD2rIyDACzY2vEo0EZUcGl9QkYgoP0qlwNdfn8e0aceRkaEAAOjry7FsWWeMHdscOjrsNSaikoWFEBEVmmvXnmDSpF+gVL66T1jDhtbYtasPGjSwljgZEVHeNL7XGBFRfho1ssHMmW0AABMntsSFC8NZBBFRiaa9PUIc2E303l6+zIKBQTm1Q17+/u7o0qU62ratJmEyIqKCYY8QEb2TsLBHaNJkI1asOKfWrqsrZxFERKXGOxVCf/zxBwYOHIhWrVrh4cOHAIAdO3bgzJkzhRqOiEoehUKJpUvPoGXL7xEZ+QyzZv2GS5d4hXkiKp00LoT2798PT09PGBoa4vLly8jIyAAAJCYmYtGiRYUekIhKjpiYRHTqtB3Tp59AdrYSAODsXAkmJnoSJyMiejcaF0ILFizAhg0bsHnzZujq6qraW7dujUuXLhVqOCIqOfbsuQFn5w04ffofAK+G2c2Y0Qbnzg1FrVoVJE5HRPRuNB4sHRERgXbt2uVqNzc3x4sXLwojExGVIElJGRg//ii2bbuiarO3N8OOHb3h7u4gXTAiokKgcSFkY2ODO3fuwMHBQa39zJkzcHJyKqxcRFQCRETEo1u3XYiKSlC1eXvXx4YNH8LCwkDCZEREhUPjQ2PDhw/H559/jvPnz0Mmk+HRo0fYuXMnpkyZglGjRhVFRiKSSJUqZihX7tWfCVNTPWzf7oUff+zDIoiIygyNC6Hp06fDx8cHnTp1QkpKCtq1a4dhw4ZhxIgRGDdu3DuFWLduHRwcHGBgYIAWLVrgwoULBVpu9+7dkMlk8PLyeqftEtGbGRvrYdeuj9C+vQOuXBkJX99GvLkyEZUpMiGEeJcFMzMzcefOHaSkpKBevXowMXm3GykGBgZi0KBB2LBhA1q0aIHVq1dj7969iIiIgLV1/lekjY6ORps2beDk5ITy5cvjp59+KtD2kpKSYG5ujsTtnWDme/ydMhOVRUII7NhxFa1b26N69fK5prEAIiIpqb6/ExNhZmZWaOt95wsq6unpoV69emjevPk7F0EAsHLlSgwfPhxDhgxBvXr1sGHDBhgZGWHLli35LqNQKDBgwADMnz+f45KICkFCQhr6998PP7+fMGBAELKyFGrTWQQRUVml8WDpDh06vPGP4m+//VbgdWVmZiIsLAwzZsxQteno6MDDwwOhoaH5Lve///0P1tbWGDp0KP744483biMjI0N1rSPgVUX5Cv+wEwHAqVPR8PU9gAcPXn02zp9/iEOHItG7d12JkxERFT2NC6HGjRurPc7KykJ4eDiuX78OPz8/jdYVHx8PhUKBSpUqqbVXqlQJt2/fznOZM2fO4Pvvv0d4eHiBtrF48WLMnz9fo1xE2iAzUwF//5NYtuwscg6QW1oaYNOmHiyCiEhraFwIrVq1Ks/2efPmISUl5b0DvUlycjJ8fX2xefNmWFlZFWiZGTNmYNKkSarHSUlJsLe3L6qIRKVCREQ8fHyC1G6N0aGDA7Zv740qVQrv2DsRUUlXaHefHzhwIJo3b46vvvqqwMtYWVlBLpfjyZMnau1PnjyBjY1Nrvnv3r2L6Oho9OjRQ9WmVL66zH+5cuUQERGB6tWrqy2jr68PfX19TZ4KUZklhMCmTWGYODEEaWnZAABdXR0sXNgRkye7qd1FnohIGxRaIRQaGgoDA82uLaKnpwdXV1ecOHFCdQq8UqnEiRMnMHbs2Fzz16lTB9euXVNrmz17NpKTk7FmzRr29BC9xeXLsRg58rDqce3aFbBrVx+4uNhKmIqISDoaF0IfffSR2mMhBB4/foyLFy9izpw5GgeYNGkS/Pz80LRpUzRv3hyrV69GamoqhgwZAgAYNGgQ7OzssHjxYhgYGKBBgwZqy1tYWABArnYiys3FxRaTJrXEypV/YtSopvjqqy4wMtJ9+4JERGWUxoWQubm52mMdHR3Url0b//vf/9ClSxeNA3h7eyMuLg7+/v6IjY1F48aNcezYMdUA6vv370NH553P8ifSahkZ2dDTk6ud6bloUSd07VoDnTtXf8OSRETaQaMLKioUCpw9exYNGzaEpaVlUeYqMv9eUNEDZr6/Sh2HqMhcu/YEPj5BGDWqKUaPbiZ1HCKi91IiLqgol8vRpUsX3mWeqARTKgXWrPkTzZptxvXrTzF58i+4eTNO6lhERCWSxofGGjRogKioKDg6OhZFHiJ6D48fJ2PIkIMICbmraqtZs/wbliAi0m4aD75ZsGABpkyZgkOHDuHx48dISkpS+0dE0jh48DacnTeoFUETJ7bEhQvDUa9eRQmTERGVXAXuEfrf//6HyZMno1u3bgCAnj17qg3AzLkpo0KhyG8VJQsvl0JlRGpqJiZP/gUbN4ap2mxtTRAQ4IUuXTggmojoTQpcCM2fPx8jR47EyZMnizIPEWkgMvIZevT4EZGRz1RtXl51sHlzD1hZGUmYjIiodChwIZRzcpm7u3uRhSEizVSqZIzMzFe9sEZGulizpiuGDm3Cu8UTERWQRmOE+MeVqGQxNzfADz/0RosWdrh8eQSGDXPh55SISAManTVWq1att/6Rff78+XsFIqL87d17Ay1bVoG9/b8XNm3duipCQ4eyACIiegcaFULz58/PdWVpIip6SUkZGD/+KLZtu4L27R1w/Lgv5PJ/O3RZBBERvRuNCqH+/fvD2tq6qLIQUR5CQ2MwcOABREUlAABOnYrGoUOR6NWrjsTJiIhKvwKPEeIvTqLilZ2txPz5p9C27VZVEWRqqoft273Qs2dtidMREZUNGp81RkRFLyoqAQMHBiE09IGqzc3NHj/80BuOjqXzPn9ERCVRgQshpVJZlDmICK9+cOzYcRVjxx5BcnImAEAul8Hf3x0zZ7ZFuXIaXwyeiIjeQON7jRFR0bl48RH8/H5SPXZyssTOnR+hZcsq0oUiIirDtPjnJcc8UcnTrJkdRoxwBQAMHtwY4eEjWAQRERUh9ggRSSgrS4Fy5XTUTkZYsaILunWryQHRRETFQIt7hIikFRERj5Ytv8e2bVfU2o2N9VgEEREVExZCRMVMCIGNGy+iSZONuHTpMcaNO4o7d3hFdiIiKfDQGFExiotLxbBhPyM4OELVZmdnirS0LAlTERFpLxZCRMUkJOQOBg8+iNjYFFXbyJGuWLHCE0ZGuhImIyLSXiyEiIpYeno2Zsw4jtWrz6varKyMsGVLT/TowbFARERSYiFEVITu3HmOjz4KxLVrT1VtXbvWwNatvWBjYyJhMiIiAlgIERUpS0sDPHuWBgDQ15dj+fLOGDu2Oe/dR0RUQvCsMaIiVKGCEQICeqFRo0q4ePEzjBvXgkUQEVEJwh4hokL0888RaNbMTu2wV+fO1REW5gi5nL87iIhKGu39y8xf5VSIUlMzMXLkIfTsuRuffnoQQgi16SyCiIhKJv51JnpPYWGP4OKyCRs3hgEAjh69g0OHIiVORUREBcFCiOgdKRRKLF16Bi1bfo/IyGcAACMjXWze3AMfflhL4nRERFQQHCNE9A5iYhLh63sAp0//o2pzdbXFrl19UKtWBQmTERGRJlgIEWkoMPA6Ro48jBcv0gG8Gm42fXobzJvXHnp6conTERGRJlgIEWngzz8foH///arH9vZm2LGjN9zdHaQLRURE74xjhIg00LJlFfj6OgMAvL3r48qVkSyCiIhKMfYIEb2BUimgo6N+qYVvvumG7t1rol+/+rw4IhFRKcceIaJ8REUloE2bLdiz54Zau5mZPry9G7AIIiIqA9gjRPQaIQR27LiKsWOPIDk5E7duHUKrVlVgb28udTQiIipk7BEi+o+EhDT0778ffn4/ITk5EwBQvryh6sapRERUtmhxjxAPa5C6U6ei4et7AA8eJKnaBg9ujLVru8LUVF/CZEREVFS0uBAieiUzUwF//5NYtuwscm4RZmFhgE2bPkTfvvWlDUdEREWKhRBptaioBPTtuxeXLj1WtbVv74Dt2704JoiISAtwjBBpNUPDcrh/PxEAoKurg2XLPHDixCAWQUREWoKFEGk1W1tTfP99T9SpY4U//xyGqVNb57puEBERlV08NEZa5fjxKDRpYoMKFYxUbT171sYHH9SAri7vE0ZEpG3YI0RaIT09GxMnHkPnzjswYsQhiJxR0f+PRRARkXZiIURl3rVrT9C8+WasXn0eALB//y0cO3ZH4lRERFQSsBCiMkupFFiz5k80a7YZ1649BQDo68uxdm1XdO1aQ+J0RERUEnCMEJVJjx8nY8iQgwgJuatqa9jQGrt29UGDBtYSJiMiopKEhRCVOcHBERg6NBjx8S9VbRMntsSiRZ1gYMC3PBER/UuLvxV4inRZdPbsffTqtVv12MbGBNu2eaFLl+oSpiIiopKKY4SoTHFzs0fv3nUAAL161ca1a6NYBBERUb60uEeIygIhBGSyf3v3ZDIZNm/ugZ49a8PPr5HaNCIiotexR4hKrZiYRHTsuB2HDkWqtVeoYITBgxuzCCIiordijxCVSnv23MCIEYfw4kU6btx4iqtXR8HGxkTqWEREVMqwR4hKlaSkDAwe/BO8vffhxYt0AICBQTk8epQscTIiIiqN2CNEpUZoaAwGDAjCvXsvVG3e3vWxfn13WFoaSheMiIhKLRZCVOJlZyuxYMHvWLDgdygUr+4RZmqqh3XrumHgQGeOBSIionfGQohKtOjoF/Dx2Y/Q0AeqNjc3e/zwQ284OlpKmIyIiMoCjhGiEk1HR4abN+MAAHK5DPPnt8fp04NZBBERUaFgIUQlWtWq5tiw4UM4OVnizJlP4e/vjnLl+LYlIqLCob3fKBxXUiL98cc/SErKUGvr378BbtwYjZYtq0iUioiIyqoSUQitW7cODg4OMDAwQIsWLXDhwoV85928eTPatm0LS0tLWFpawsPD443zU+mQmanA9OnH4e4egHHjjuaazpulEhFRUZC8EAoMDMSkSZMwd+5cXLp0CY0aNYKnpyeePn2a5/ynTp3CJ598gpMnTyI0NBT29vbo0qULHj58WMzJqbBERMSjVavvsXTpWQgBbN9+Bb/8clfqWEREpAVkQgghZYAWLVqgWbNm+OabbwAASqUS9vb2GDduHKZPn/7W5RUKBSwtLfHNN99g0KBBb50/KSkJ5ubmSNz5Acx8jrx3fnp3Qghs2hSGiRNDkJaWDQDQ1dXBwoUdMXmyG3R0ePiSiIheUX1/JybCzMys0NYr6fGGzMxMhIWFYcaMGao2HR0deHh4IDQ0tEDrePnyJbKyslC+fPk8p2dkZCAj498xJ0lJSe8XmgpFXFwqhg37GcHBEaq22rUrYNeuPnBxsZUwGRERaRNJD43Fx8dDoVCgUqVKau2VKlVCbGxsgdYxbdo0VK5cGR4eHnlOX7x4MczNzVX/7O3t3zs3vZ+QkDtwdt6gVgSNGtUUly6NYBFERETFSvIxQu9jyZIl2L17Nw4cOAADA4M855kxYwYSExNV/2JiYoo5Jf3XH3/8g65ddyI2NgUAYGVlhODg/vj22+4wMtKVOB0REWkbSQ+NWVlZQS6X48mTJ2rtT548gY2NzRuX/eqrr7BkyRIcP34czs7O+c6nr68PfX39QslL769Nm6ro2rUGjh27g65da2Dr1l68azwREUlG0h4hPT09uLq64sSJE6o2pVKJEydOoFWrVvkut2zZMnz55Zc4duwYmjZtWhxRqZDIZDJs3doL337bDUeO+LAIIiIiSUl+aGzSpEnYvHkztm3bhlu3bmHUqFFITU3FkCFDAACDBg1SG0y9dOlSzJkzB1u2bIGDgwNiY2MRGxuLlJQUqZ4C5SM2NgXdu+/CiRNRau02NiYYNaoZb5ZKRESSk/wqdd7e3oiLi4O/vz9iY2PRuHFjHDt2TDWA+v79+9DR+bdeW79+PTIzM/Hxxx+rrWfu3LmYN29ecUanNwgOjsDQocGIj3+JK1diceXKSFSoYCR1LCIiIjWSX0eouP17HaFuMPM5LHWcMic1NROTJ/+CjRvDVG22tib4+edP4OpaWcJkRERUmpXJ6whR2RIW9ggDBgQhIuKZqs3Lqw42b+4BKyv2BhERUcnDQojem0KhxFdfncPs2SeRna0EABgZ6WLNmq4YOrQJxwIREVGJxUKI3suDB0nw9T2AU6eiVW2urrbYtasPatWqIF0wIiKiApD8rDEq3dLSsvDXX69ueCuTATNmtMG5c0NZBBERUanAQojeS82aFbB27QewtzfDyZN+WLSoE/T05FLHIiIiKhAWQqSRCxce4uXLLLW2IUMa4+bNMXB3d5AmFBER0TtiIUQFkp2txPz5p+Dm9j2mTPlFbZpMJoOJiZ5EyYiIiN4dCyF6q6ioBLRrtxXz5p2GQiGwfv1FnDx5T+pYRERE741njVG+hBDYseMqxo49guTkTACAXC6Dv7872ratJnE6IiKi98dCiPKUkJCGUaMOIzDwhqrNyckSO3d+hJYtq0iYjIiIqPBobyHEi/zl6/TpaPj6HkBMTJKqbfDgxli7titMTfUlTEZERFS4tLcQojydPh2NDh22IecOdJaWBti48UP07Vtf2mBERERFgIOlSU2bNlXRrt2r8T8dOjjg6tVRLIKIiKjMYo8QqZHLdbBjR2/s3XsTEya0hI4ODyESEVHZxR4hLRYXl4o+ffbg7Nn7au329uaYNKkViyAiIirz2COkpUJC7mDw4IOIjU3BpUuPceXKSJiZcSA0ERFpF/YIaZn09GxMmHAMXbvuRGxsCgAgJSUTkZHPJE5GRERU/NgjpEWuXXsCH58gXL/+VNXWtWsNbN3aCzY2JhImIyIikgYLIS2gVAp8/fV5TJt2HBkZCgCAvr4cy5d3xtixzSHjNZWIiEhLsRAq4x4/TsaQIQcREnJX1dawoTV27eqDBg2sJUxGREQkPY4RKuOeP0/DqVPRqscTJ7bEhQvDWQQRERFBqwsh7TgcVL++NZYv7wwbGxOEhAzEypWeMDBgRyARERGg1YVQ2XTlSiwyMrLV2saObY6bN0ejS5fqEqUiIiIqmVgIlREKhRJLl55B06abMWvWb2rTZDIZLC0NJUpGRERUcrEQKgNiYhLRqdN2TJ9+AtnZSqxYEYozZ+6/fUEiIiItx8EipdyePTcwYsQhvHiRDgCQyYDp09ugeXM7iZMRERGVfCyESqmkpAyMH38U27ZdUbXZ25thx47ecHd3kC4YERFRKcJCqBQKDY3BwIEHEBWVoGrz9q6P9eu7cywQERGRBlgIlTKnTkXDw2M7FAoBADA11cO6dd0wcKAzrxBNRESkIQ6WLmVat7aHq2tlAICbmz2uXBkJX99GLIKIiIjeAXuEShldXTl27vwIgYHXMW1aG5Qrx1qWiIjoXbEQKsESEtIwduxRTJrUUtULBAA1apTHrFntJExGpF2EEMjOzoZCoZA6ClGZpqurC7lcXqzb1N5CqIQfSjp1Khq+vgfw4EESwsIe4dKlETAy0pU6FpHWyczMxOPHj/Hy5UupoxCVeTKZDFWqVIGJiUmxbVN7C6ESKjNTAX//k1i27CzEq/HQePo0FTduPEWzZrw2EFFxUiqVuHfvHuRyOSpXrgw9PT2OxyMqIkIIxMXF4cGDB6hZs2ax9QyxECpBIiLi4eMThEuXHqvaOnRwwPbtvVGlipmEyYi0U2ZmJpRKJezt7WFkZCR1HKIyr2LFioiOjkZWVhYLIW0ihMCmTWGYODEEaWmvbpiqq6uDhQs7YvJkN+jo8BcokZR0dHhSAlFxkKLHlYWQxOLiUjFs2M8IDo5QtdWuXQG7dvWBi4uthMmIiIjKPhZCEouJScKRI3+rHo8a1RRffdWFA6OJiIiKAft7JebiYosFCzrAysoIwcH98e233VkEERFJKCIiAjY2NkhOTpY6SpmSmZkJBwcHXLx4UeooalgIFbPbt+ORlaV+LZIpU9xw48Zo9OhRW6JURFTWDB48GDKZDDKZDLq6unB0dMQXX3yB9PT0XPMeOnQI7u7uMDU1hZGREZo1a4aAgIA817t//360b98e5ubmMDExgbOzM/73v//h+fPnRfyMis+MGTMwbtw4mJqaSh2lSPz+++/o0aMHKleuDJlMhp9++qlAy506dQouLi7Q19dHjRo18nyPrFu3Dg4ODjAwMECLFi1w4cIF1TQ9PT1MmTIF06ZNK6RnUjhYCBUTpVJgzZo/0bjxBixY8LvaNLlcB9bWxhIlI6KyqmvXrnj8+DGioqKwatUqbNy4EXPnzlWb5+uvv0avXr3QunVrnD9/HlevXkX//v0xcuRITJkyRW3eWbNmwdvbG82aNcPRo0dx/fp1rFixAleuXMGOHTuK7XllZmYW2brv37+PQ4cOYfDgwe+1nqLM+L5SU1PRqFEjrFu3rsDL3Lt3D927d0eHDh0QHh6OCRMmYNiwYQgJCVHNExgYiEmTJmHu3Lm4dOkSGjVqBE9PTzx9+lQ1z4ABA3DmzBncuHGjUJ/TexFaJjExUQAQiT/2KLZtPnqUJDw9dwhgngDmCR2d+eL8+QfFtn0iejdpaWni5s2bIi0tTeooGvPz8xO9evVSa/voo49EkyZNVI/v378vdHV1xaRJk3Itv3btWgFA/Pnnn0IIIc6fPy8AiNWrV+e5vYSEhHyzxMTEiP79+wtLS0thZGQkXF1dVevNK+fnn38u3N3dVY/d3d3FmDFjxOeffy4qVKgg2rdvLz755BPRr18/teUyMzNFhQoVxLZt24QQQigUCrFo0SLh4OAgDAwMhLOzs9i7d2++OYUQYvny5aJp06ZqbfHx8aJ///6icuXKwtDQUDRo0EDs2rVLbZ68MgohxLVr10TXrl2FsbGxsLa2FgMHDhRxcXGq5Y4ePSpat24tzM3NRfny5UX37t3FnTt33pixMAEQBw4ceOt8X3zxhahfv75am7e3t/D09FQ9bt68uRgzZozqsUKhEJUrVxaLFy9WW65Dhw5i9uzZeW7nTZ851fd3YuJb82qCg6WL2MGDtzFs2M+Ij//3qrTjxzeHs3MlCVMR0Xv5oSmQGlv82zW2AQa+2/iK69ev49y5c6hWrZqqbd++fcjKysrV8wMAI0aMwMyZM/Hjjz+iRYsW2LlzJ0xMTDB69Og8129hYZFne0pKCtzd3WFnZ4fg4GDY2Njg0qVLUCqVGuXftm0bRo0ahbNnzwIA7ty5g759+yIlJUV1FeKQkBC8fPkSvXv3BgAsXrwYP/zwAzZs2ICaNWvi999/x8CBA1GxYkW4u7vnuZ0//vgDTZs2VWtLT0+Hq6srpk2bBjMzMxw+fBi+vr6oXr06mjdvnm/GFy9eoGPHjhg2bBhWrVqFtLQ0TJs2Df369cNvv/0G4FXvzKRJk+Ds7IyUlBT4+/ujd+/eCA8Pz/eyDYsWLcKiRYve+HrdvHkTVatWfdvLWmChoaHw8PBQa/P09MSECRMAvOoBCwsLw4wZM1TTdXR04OHhgdDQULXlmjdvjj/++KPQsr0vLS6EivZaBampmZg8+Rds3BimarOxMcG2bV7o0qV6kW6biIpYaiyQ8lDqFG916NAhmJiYIDs7GxkZGdDR0cE333yjmh4ZGQlzc3PY2ua+VIeenh6cnJwQGRkJAPj777/h5OQEXV3NTubYtWsX4uLi8Ndff6F8+fIAgBo1amj8XGrWrIlly5apHlevXh3GxsY4cOAAfH19Vdvq2bMnTE1NkZGRgUWLFuH48eNo1aoVAMDJyQlnzpzBxo0b8y2E/vnnn1yFkJ2dnVqxOG7cOISEhGDPnj1qhdDrGRcsWIAmTZqoFS1btmyBvb09IiMjUatWLfTp00dtW1u2bEHFihVx8+ZNNGjQIM+MI0eORL9+/d74elWuXPmN0zUVGxuLSpXUf8BXqlQJSUlJSEtLQ0JCAhQKRZ7z3L59O1e2f/75p1DzvQ8tLoSKTljYI/j4BCEy8pmqrVev2vjuu56wsuLVaYlKPWObUrHdDh06YP369UhNTcWqVatQrly5XF+8BSVy7vmjofDwcDRp0kRVBL0rV1dXtcflypVDv379sHPnTvj6+iI1NRUHDx7E7t27AbzqMXr58iU6d+6stlxmZiaaNGmS73bS0tJgYGCg1qZQKLBo0SLs2bMHDx8+RGZmJjIyMnJdbfz1jFeuXMHJkyfzvG/W3bt3UatWLfz999/w9/fH+fPnER8fr+opu3//fr6FUPny5d/79ZSSoaFhibp3HwuhQvbbb/fg6fkDsrNfvZmNjHSxerUnhg1z4T2KiMqKdzw8VdyMjY1VvS9btmxBo0aN8P3332Po0KEAgFq1aiExMRGPHj3K1YOQmZmJu3fvokOHDqp5z5w5g6ysLI16hQwNDd84XUdHJ1eRlZWVledzed2AAQPg7u6Op0+f4tdff4WhoSG6du0K4NUhOQA4fPgw7OzU79Oor6+fbx4rKyskJCSotS1fvhxr1qzB6tWr0bBhQxgbG2PChAm5BkS/njElJQU9evTA0qVLc20npxeuR48eqFatGjZv3ozKlStDqVSiQYMGbxxsLcWhMRsbGzx58kSt7cmTJzAzM4OhoSHkcjnkcnme89jYqBfwz58/R8WKFQst2/viWWOFrHVre9Sr92oHu7ra4vLlERg+3JVFEBFJSkdHBzNnzsTs2bORlpYGAOjTpw90dXWxYsWKXPNv2LABqamp+OSTTwAAPj4+SElJwbfffpvn+l+8eJFnu7OzM8LDw/M9vb5ixYp4/PixWlt4eHiBnpObmxvs7e0RGBiInTt3om/fvqoirV69etDX18f9+/dRo0YNtX/29vb5rrNJkya4efOmWtvZs2fRq1cvDBw4EI0aNVI7ZPgmLi4uuHHjBhwcHHJlMDY2xrNnzxAREYHZs2ejU6dOqFu3bq4iLC8jR45EeHj4G/8V9qGxVq1a4cSJE2ptv/76q+qwo56eHlxdXdXmUSqVOHHihGqeHNevX39jr1yxK9Sh16XAv2eN9SyybVy//kTMmnVCZGRkF9k2iKjolbWzxrKysoSdnZ1Yvny5qm3VqlVCR0dHzJw5U9y6dUvcuXNHrFixQujr64vJkyerLf/FF18IuVwupk6dKs6dOyeio6PF8ePHxccff5zv2WQZGRmiVq1aom3btuLMmTPi7t27Yt++feLcuXNCCCGOHTsmZDKZ2LZtm4iMjBT+/v7CzMws11ljn3/+eZ7rnzVrlqhXr54oV66c+OOPP3JNq1ChgggICBB37twRYWFhYu3atSIgICDf1y04OFhYW1uL7Ox//35PnDhR2Nvbi7Nnz4qbN2+KYcOGCTMzM7XXN6+MDx8+FBUrVhQff/yxuHDhgrhz5444duyYGDx4sMjOzhYKhUJUqFBBDBw4UPz999/ixIkTolmzZgU+k+tdJScni8uXL4vLly8LAGLlypXi8uXL4p9//lHNM336dOHr66t6HBUVJYyMjMTUqVPFrVu3xLp164RcLhfHjh1TzbN7926hr68vAgICxM2bN8Vnn30mLCwsRGxsrNr2q1WrJrZv355nNinOGmMh9F7rShfDhh0U168/KYRkRFTSlLVCSAghFi9eLCpWrChSUlJUbQcPHhRt27YVxsbGwsDAQLi6uootW7bkud7AwEDRrl07YWpqKoyNjYWzs7P43//+98bT56Ojo0WfPn2EmZmZMDIyEk2bNhXnz59XTff39xeVKlUS5ubmYuLEiWLs2LEFLoRu3rwpAIhq1aoJpVKpNk2pVIrVq1eL2rVrC11dXVGxYkXh6ekpTp8+nW/WrKwsUblyZbUv+GfPnolevXoJExMTYW1tLWbPni0GDRr01kJICCEiIyNF7969hYWFhTA0NBR16tQREyZMUGX99ddfRd26dYW+vr5wdnYWp06dKvJC6OTJkwJArn9+fn6qefz8/NT2Qc5yjRs3Fnp6esLJyUls3bo117q//vprUbVqVaGnpyeaN2+uukxCjnPnzgkLCwvx8uXLPLNJUQjJhHjHEXClVFJSEszNzZH4Y0+Y9T/4zusJDY3BwIEHEBWVAGfnSrhwYRj09TnkiqgsSU9Px7179+Do6JhrAC2VXevWrUNwcLDaxQKpcHh7e6NRo0aYOXNmntPf9JlTfX8nJsLMzKzQMnGMkIays5WYP/8U2rbdiqioV8dy791LwNWrT96yJBERlQYjRoxAu3bteK+xQpaZmYmGDRti4sSJUkdRwy4MDURFJWDgwCCEhj5Qtbm52eOHH3rD0dFSwmRERFRYypUrh1mzZkkdo8zR09PD7NmzpY6RCwuhAhBCYMeOqxg79giSk1+d0iiXy+Dv746ZM9uiXDl2rBEREZVGLITeIiEhDaNGHUZg4L83iHNyssTOnR+hZcsqEiYjIiKi96W9hVABr+tz61Y89u7995oSgwc3xtq1XWFqmv8FuYiobNGyc0qIJCPFZ43HdN7Czc0es2a1hYWFAfbs+Rhbt/ZiEUSkJXIuzleSbgdAVJblXFFbLpcX2za1t0coH/fuJaBqVXPI5f/WiHPmtMOIEa6wsyu80/WIqOSTy+WwsLDA06dPAQBGRka8SjxREVEqlYiLi4ORkRHKlSu+8oSF0P8TQmDTpjBMnBiCuXPdMW1aG9U0XV05iyAiLZVzn6ScYoiIio6Ojg6qVq1arD84WAgBiItLxbBhPyM4OAIAMHv2SXTpUh1NmthKnIyIpCaTyWBrawtra+s8bwZKRIVHT08POjrFO2qnRBRC69atw/LlyxEbG4tGjRrh66+/RvPmzfOdf+/evZgzZw6io6NRs2ZNLF26FN26dXunbYeE3MHgwQcRG5uiahs2rAlq17Z6p/URUdmUc3dtIipbJB8sHRgYiEmTJmHu3Lm4dOkSGjVqBE9Pz3y7oc+dO4dPPvkEQ4cOxeXLl+Hl5QUvLy9cv35do+2mZ8owYcIxdO26U1UEWVkZITi4P9av/xBGRrrv/dyIiIioZJP8XmMtWrRAs2bN8M033wB4NVjK3t4e48aNw/Tp03PN7+3tjdTUVBw6dEjV1rJlSzRu3BgbNmx46/Zy7lVS134ibsWYq9q7dq2BrVt7wcbGpBCeFRERERWmMnmvsczMTISFhcHDw0PVpqOjAw8PD4SGhua5TGhoqNr8AODp6Znv/Pm5FfPqFHh9fTnWru2KI0d8WAQRERFpGUnHCMXHx0OhUKBSpUpq7ZUqVcLt27fzXCY2NjbP+WNjY/OcPyMjAxkZGarHiYmJOVNQr15FfP99L9SrV5E31yMiIirBkpKSABT+RRdLxGDporR48WLMnz8/jymrcPMm0KrV5GLPRERERO/m2bNnMDc3f/uMBSRpIWRlZQW5XI4nT56otT958kR17Y7X2djYaDT/jBkzMGnSJNXjFy9eoFq1arh//36hvpCkuaSkJNjb2yMmJqZQj/fSu+H+KDm4L0oO7ouSIzExEVWrVkX58uULdb2SFkJ6enpwdXXFiRMn4OXlBeDVYOkTJ05g7NixeS7TqlUrnDhxAhMmTFC1/frrr2jVqlWe8+vr60NfP/ctMczNzfmmLiHMzMy4L0oQ7o+Sg/ui5OC+KDkK+zpDkh8amzRpEvz8/NC0aVM0b94cq1evRmpqKoYMGQIAGDRoEOzs7LB48WIAwOeffw53d3esWLEC3bt3x+7du3Hx4kVs2rRJyqdBREREpZDkhZC3tzfi4uLg7++P2NhYNG7cGMeOHVMNiL5//75a9efm5oZdu3Zh9uzZmDlzJmrWrImffvoJDRo0kOopEBERUSkleSEEAGPHjs33UNipU6dytfXt2xd9+/Z9p23p6+tj7ty5eR4uo+LFfVGycH+UHNwXJQf3RclRVPtC8gsqEhEREUlF8ltsEBEREUmFhRARERFpLRZCREREpLVYCBEREZHWKpOF0Lp16+Dg4AADAwO0aNECFy5ceOP8e/fuRZ06dWBgYICGDRviyJEjxZS07NNkX2zevBlt27aFpaUlLC0t4eHh8dZ9R5rR9LORY/fu3ZDJZKoLn9L703RfvHjxAmPGjIGtrS309fVRq1Yt/q0qJJrui9WrV6N27dowNDSEvb09Jk6ciPT09GJKW3b9/vvv6NGjBypXrgyZTIaffvrprcucOnUKLi4u0NfXR40aNRAQEKD5hkUZs3v3bqGnpye2bNkibty4IYYPHy4sLCzEkydP8pz/7NmzQi6Xi2XLlombN2+K2bNnC11dXXHt2rViTl72aLovfHx8xLp168Tly5fFrVu3xODBg4W5ubl48OBBMScvmzTdHznu3bsn7OzsRNu2bUWvXr2KJ2wZp+m+yMjIEE2bNhXdunUTZ86cEffu3ROnTp0S4eHhxZy87NF0X+zcuVPo6+uLnTt3inv37omQkBBha2srJk6cWMzJy54jR46IWbNmiaCgIAFAHDhw4I3zR0VFCSMjIzFp0iRx8+ZN8fXXXwu5XC6OHTum0XbLXCHUvHlzMWbMGNVjhUIhKleuLBYvXpzn/P369RPdu3dXa2vRooUYMWJEkebUBprui9dlZ2cLU1NTsW3btqKKqFXeZX9kZ2cLNzc38d133wk/Pz8WQoVE032xfv164eTkJDIzM4srotbQdF+MGTNGdOzYUa1t0qRJonXr1kWaU9sUpBD64osvRP369dXavL29haenp0bbKlOHxjIzMxEWFgYPDw9Vm46ODjw8PBAaGprnMqGhoWrzA4Cnp2e+81PBvMu+eN3Lly+RlZVV6DfY00bvuj/+97//wdraGkOHDi2OmFrhXfZFcHAwWrVqhTFjxqBSpUpo0KABFi1aBIVCUVyxy6R32Rdubm4ICwtTHT6LiorCkSNH0K1bt2LJTP8qrO/vEnFl6cISHx8PhUKhuj1HjkqVKuH27dt5LhMbG5vn/LGxsUWWUxu8y7543bRp01C5cuVcb3TS3LvsjzNnzuD7779HeHh4MSTUHu+yL6KiovDbb79hwIABOHLkCO7cuYPRo0cjKysLc+fOLY7YZdK77AsfHx/Ex8ejTZs2EEIgOzsbI0eOxMyZM4sjMv1Hft/fSUlJSEtLg6GhYYHWU6Z6hKjsWLJkCXbv3o0DBw7AwMBA6jhaJzk5Gb6+vti8eTOsrKykjqP1lEolrK2tsWnTJri6usLb2xuzZs3Chg0bpI6mdU6dOoVFixbh22+/xaVLlxAUFITDhw/jyy+/lDoavaMy1SNkZWUFuVyOJ0+eqLU/efIENjY2eS5jY2Oj0fxUMO+yL3J89dVXWLJkCY4fPw5nZ+eijKk1NN0fd+/eRXR0NHr06KFqUyqVAIBy5cohIiIC1atXL9rQZdS7fDZsbW2hq6sLuVyuaqtbty5iY2ORmZkJPT29Is1cVr3LvpgzZw58fX0xbNgwAEDDhg2RmpqKzz77DLNmzVK7STgVrfy+v83MzArcGwSUsR4hPT09uLq64sSJE6o2pVKJEydOoFWrVnku06pVK7X5AeDXX3/Nd34qmHfZFwCwbNkyfPnllzh27BiaNm1aHFG1gqb7o06dOrh27RrCw8NV/3r27IkOHTogPDwc9vb2xRm/THmXz0br1q1x584dVTEKAJGRkbC1tWUR9B7eZV+8fPkyV7GTU6AK3rqzWBXa97dm47hLvt27dwt9fX0REBAgbt68KT777DNhYWEhYmNjhRBC+Pr6iunTp6vmP3v2rChXrpz46quvxK1bt8TcuXN5+nwh0XRfLFmyROjp6Yl9+/aJx48fq/4lJydL9RTKFE33x+t41ljh0XRf3L9/X5iamoqxY8eKiIgIcejQIWFtbS0WLFgg1VMoMzTdF3PnzhWmpqbixx9/FFFRUeKXX34R1atXF/369ZPqKZQZycnJ4vLly+Ly5csCgFi5cqW4fPmy+Oeff4QQQkyfPl34+vqq5s85fX7q1Kni1q1bYt26dTx9PsfXX38tqlatKvT09ETz5s3Fn3/+qZrm7u4u/Pz81Obfs2ePqFWrltDT0xP169cXhw8fLubEZZcm+6JatWoCQK5/c+fOLf7gZZSmn43/YiFUuDTdF+fOnRMtWrQQ+vr6wsnJSSxcuFBkZ2cXc+qySZN9kZWVJebNmyeqV68uDAwMhL29vRg9erRISEgo/uBlzMmTJ/P8Dsh5/f38/IS7u3uuZRo3biz09PSEk5OT2Lp1q8bblQnBvjwiIiLSTmVqjBARERGRJlgIERERkdZiIURERERai4UQERERaS0WQkRERKS1WAgRERGR1mIhRERERFqLhRARqQkICICFhYXUMd6ZTCbDTz/99MZ5Bg8eDC8vr2LJQ0QlGwshojJo8ODBkMlkuf7duXNH6mgICAhQ5dHR0UGVKlUwZMgQPH36tFDW//jxY3zwwQcAgOjoaMhkMoSHh6vNs2bNGgQEBBTK9vIzb9481fOUy+Wwt7fHZ599hufPn2u0HhZtREWrTN19noj+1bVrV2zdulWtrWLFihKlUWdmZoaIiAgolUpcuXIFQ4YMwaNHjxASEvLe687vruH/ZW5u/t7bKYj69evj+PHjUCgUuHXrFj799FMkJiYiMDCwWLZPRG/HHiGiMkpfXx82NjZq/+RyOVauXImGDRvC2NgY9vb2GD16NFJSUvJdz5UrV9ChQweYmprCzMwMrq6uuHjxomr6mTNn0LZtWxgaGsLe3h7jx49HamrqG7PJZDLY2NigcuXK+OCDDzB+/HgcP34caWlpUCqV+N///ocqVapAX18fjRs3xrFjx1TLZmZmYuzYsbC1tYWBgQGqVauGxYsXq60759CYo6MjAKBJkyaQyWRo3749APVelk2bNqFy5cpqd3YHgF69euHTTz9VPT548CBcXFxgYGAAJycnzJ8/H9nZ2W98nuXKlYONjQ3s7Ozg4eGBvn374tdff1VNVygUGDp0KBwdHWFoaIjatWtjzZo1qunz5s3Dtm3bcPDgQVXv0qlTpwAAMTEx6NevHywsLFC+fHn06tUL0dHRb8xDRLmxECLSMjo6Oli7di1u3LiBbdu24bfffsMXX3yR7/wDBgxAlSpV8NdffyEsLAzTp0+Hrq4uAODu3bvo2rUr+vTpg6tXryIwMBBnzpzB2LFjNcpkaGgIpVKJ7OxsrFmzBitWrMBXX32Fq1evwtPTEz179sTff/8NAFi7di2Cg4OxZ88eREREYOfOnXBwcMhzvRcuXAAAHD9+HI8fP0ZQUFCuefr27Ytnz57h5MmTqrbnz5/j2LFjGDBgAADgjz/+wKBBg/D555/j5s2b2LhxIwICArBw4cICP8fo6GiEhIRAT09P1aZUKlGlShXs3bsXN2/ehL+/P2bOnIk9e/YAAKZMmYJ+/fqha9euePz4MR4/fgw3NzdkZWXB09MTpqam+OOPP3D27FmYmJiga9euyMzMLHAmIgLK5N3nibSdn5+fkMvlwtjYWPXv448/znPevXv3igoVKqgeb926VZibm6sem5qaioCAgDyXHTp0qPjss8/U2v744w+ho6Mj0tLS8lzm9fVHRkaKWrVqiaZNmwohhKhcubJYuHCh2jLNmjUTo0ePFkIIMW7cONGxY0ehVCrzXD8AceDAASGEEPfu3RMAxOXLl9Xm8fPzE7169VI97tWrl/j0009Vjzdu3CgqV64sFAqFEEKITp06iUWLFqmtY8eOHcLW1jbPDEIIMXfuXKGjoyOMjY2FgYGB6k7aK1euzHcZIYQYM2aM6NOnT75Zc7Zdu3ZttdcgIyNDGBoaipCQkDeun4jUcYwQURnVoUMHrF+/XvXY2NgYwKvekcWLF+P27dtISkpCdnY20tPT8fLlSxgZGeVaz6RJkzBs2DDs2LFDdXinevXqAF4dNrt69Sp27typml8IAaVSiXv37qFu3bp5ZktMTISJiQmUSiXS09PRpk0bfPfdd0hKSsKjR4/QunVrtflbt26NK1euAHh1WKtz586oXbs2unbtig8//BBdunR5r9dqwIABGD58OL799lvo6+tj586d6N+/P3R0dFTP8+zZs2o9QAqF4o2vGwDUrl0bwcHBSE9Pxw8//IDw8HCMGzdObZ5169Zhy5YtuH//PtLS0pCZmYnGjRu/Me+VK1dw584dmJqaqrWnp6fj7t277/AKEGkvFkJEZZSxsTFq1Kih1hYdHY0PP/wQo0aNwsKFC1G+fHmcOXMGQ4cORWZmZp5f6PPmzYOPjw8OHz6Mo0ePYu7cudi9ezd69+6NlJQUjBgxAuPHj8+1XNWqVfPNZmpqikuXLkFHRwe2trYwNDQEACQlJb31ebm4uODevXs4evQojh8/jn79+sHDwwP79u1767L56dGjB4QQOHz4MJo1a4Y//vgDq1atUk1PSUnB/Pnz8dFHH+Va1sDAIN/16unpqfbBkiVL0L17d8yfPx9ffvklAGD37t2YMmUKVqxYgVatWsHU1BTLly/H+fPn35g3JSUFrq6uagVojpIyIJ6otGAhRKRFwsLCoFQqsWLFClVvR854lDepVasWatWqhYkTJ+KTTz7B1q1b0bt3b7i4uODmzZu5Cq630dHRyXMZMzMzVK5cGWfPnoW7u7uq/ezZs2jevLnafN7e3vD29sbHH3+Mrl274vnz5yhfvrza+nLG4ygUijfmMTAwwEcffYSdO3fizp07qF27NlxcXFTTXVxcEBERofHzfN3s2bPRsWNHjBo1SvU83dzcMHr0aNU8r/fo6Onp5crv4uKCwMBAWFtbw8zM7L0yEWk7DpYm0iI1atRAVlYWvv76a0RFRWHHjh3YsGFDvvOnpaVh7NixOHXqFP755x+cPXsWf/31l+qQ17Rp03Du3DmMHTsW4eHh+Pvvv3Hw4EGNB0v/19SpU7F06VIEBgYiIiIC06dPR3h4OD7//HMAwMqVK/Hjjz/i9u3biIyMxN69e2FjY5PnRSCtra1haGiIY8eO4cmTJ0hMTMx3uwMGDMDhw4exZcsW1SDpHP7+/ti+fTvmz5+PGzdu4NatW9i9ezdmz56t0XNr1aoVnJ2dsWjRIgBAzZo1cfHiRYSEhCAyMhJz5szBX3/9pbaMg4MDrl69ioiICMTHxyMrKwsDBgyAlZUVevXqhT/++AP37t3DqVOnMH78eDx48ECjTERaT+pBSkRU+PIaYJtj5cqVwtbWVhgaGgpPT0+xfft2AUAkJCQIIdQHM2dkZIj+/fsLe3t7oaenJypXrizGjh2rNhD6woULonPnzsLExEQYGxsLZ2fnXIOd/+v1wdKvUygUYt68ecLOzk7o6uqKRo0aiaNHj6qmb9q0STRu3FgYGxsLMzMz0alTJ3Hp0iXVdPxnsLQQQmzevFnY29sLHR0d4e7unu/ro1AohK2trQAg7t69myvXsWPHhJubmzA0NBRmZmaiefPmYtOmTfk+j7lz54pGjRrlav/xxx+Fvr6+uH//vkhPTxeDBw8W5ubmwsLCQowaNUpMnz5dbbmnT5+qXl8A4uTJk0IIIR4/fiwGDRokrKyshL6+vnBychLDhw8XiYmJ+WYiotxkQgghbSlGREREJA0eGiMiIiKtxUKIiIiItBYLISIiItJaLISIiIhIa7EQIiIiIq3FQoiIiIi0FgshIiIi0loshIiIiEhrsRAiIiIircVCiIiIiLQWCyEiIiLSWiyEiIiISGv9H+fVEdV4hH8kAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot ROC curve\n",
    "fpr, tpr, _ = roc_curve(y_test, y_pred_prob)\n",
    "roc_auc = auc(fpr, tpr)\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(fpr, tpr, color='darkorange', lw=2, label='ROC curve (area = {:.2f})'.format(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 (ROC) Curve')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bf303427",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:48.082908Z",
     "iopub.status.busy": "2024-01-23T14:36:48.082474Z",
     "iopub.status.idle": "2024-01-23T14:36:48.104219Z",
     "shell.execute_reply": "2024-01-23T14:36:48.103134Z"
    },
    "id": "3tW2fegZD6qu",
    "outputId": "ec73004b-0fc9-4e7c-9658-3ef820581b04",
    "papermill": {
     "duration": 0.037402,
     "end_time": "2024-01-23T14:36:48.107100",
     "exception": false,
     "start_time": "2024-01-23T14:36:48.069698",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The transaction is predicted as fraud.\n"
     ]
    }
   ],
   "source": [
    "# Collect user input\n",
    "#uncomment this for user input data\n",
    "\n",
    "user_input = {\n",
    "    'step': int(input(\"Enter the step: \")),\n",
    "    'amount': float(input(\"Enter the transaction amount: \")),\n",
    "    'oldbalanceOrg': float(input(\"Enter the old balance of the origin account: \")),\n",
    "    'newbalanceOrig': float(input(\"Enter the new balance of the origin account: \")),\n",
    "    'oldbalanceDest': float(input(\"Enter the old balance of the destination account: \")),\n",
    "    'newbalanceDest': float(input(\"Enter the new balance of the destination account: \")),\n",
    "    'isFlaggedFraud': df['isFlaggedFraud'].values[0]  # Extract from your dataset\n",
    "}\n",
    "\n",
    "user_input = {\n",
    "    'step': 1,\n",
    "    'amount': 10000.00,\n",
    "    'oldbalanceOrg': 30000.00,\n",
    "    'newbalanceOrig': 0.0,\n",
    "    'oldbalanceDest': 3000.00,\n",
    "    'newbalanceDest': 33000.00,\n",
    "    'isFlaggedFraud': df['isFlaggedFraud'].values[0]  # Extract from your dataset\n",
    "}\n",
    "# Create a DataFrame from user input\n",
    "user_df = pd.DataFrame([user_input])\n",
    "\n",
    "# Make predictions using the model\n",
    "user_predictions = model.predict(user_df)\n",
    "\n",
    "# Check if the user input resulted in fraud or not\n",
    "if user_predictions[0] == 1:\n",
    "    print(\"The transaction is predicted as fraud.\")\n",
    "else:\n",
    "    print(\"The transaction is predicted as non-fraud.\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6cdc3ca6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-01-23T14:36:48.133730Z",
     "iopub.status.busy": "2024-01-23T14:36:48.133267Z",
     "iopub.status.idle": "2024-01-23T14:36:49.549128Z",
     "shell.execute_reply": "2024-01-23T14:36:49.547908Z"
    },
    "id": "wOMNAqmdD6yD",
    "outputId": "c38a5aee-27d7-443a-8831-f0683247a1fa",
    "papermill": {
     "duration": 1.431714,
     "end_time": "2024-01-23T14:36:49.551893",
     "exception": false,
     "start_time": "2024-01-23T14:36:48.120179",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import precision_recall_curve, average_precision_score\n",
    "\n",
    "# Calculate Precision and Recall\n",
    "precision, recall, _ = precision_recall_curve(y_test, y_pred_prob)\n",
    "average_precision = average_precision_score(y_test, y_pred_prob)\n",
    "\n",
    "# Plot the Precision-Recall curve\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.step(recall, precision, where='post')\n",
    "plt.fill_between(recall, precision, step='post', alpha=0.2)\n",
    "plt.xlabel('Recall')\n",
    "plt.ylabel('Precision')\n",
    "plt.ylim([0.0, 1.05])\n",
    "plt.xlim([0.0, 1.0])\n",
    "plt.title(f'Precision-Recall Curve (AP = {average_precision:.2f})')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5942e23d",
   "metadata": {
    "id": "okWvT_eDZt-s",
    "papermill": {
     "duration": 0.01182,
     "end_time": "2024-01-23T14:36:49.575663",
     "exception": false,
     "start_time": "2024-01-23T14:36:49.563843",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2a533fa",
   "metadata": {
    "id": "DVV3T5IcUV3A",
    "papermill": {
     "duration": 0.012246,
     "end_time": "2024-01-23T14:36:49.600664",
     "exception": false,
     "start_time": "2024-01-23T14:36:49.588418",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 2580326,
     "sourceId": 4398600,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 30635,
   "isGpuEnabled": false,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 94.381,
   "end_time": "2024-01-23T14:36:50.937885",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2024-01-23T14:35:16.556885",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}