7-Hybrid sampling - smoteenn.ipynb

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BILL_AMT3  BILL_AMT4  BILL_AMT5  BILL_AMT6  PAY_AMT1  \\\n","0         -2  ...      689.0        0.0        0.0        0.0       0.0   \n","1          0  ...     2682.0     3272.0     3455.0     3261.0       0.0   \n","2          0  ...    13559.0    14331.0    14948.0    15549.0    1518.0   \n","3          0  ...    49291.0    28314.0    28959.0    29547.0    2000.0   \n","4          0  ...    35835.0    20940.0    19146.0    19131.0    2000.0   \n","...      ...  ...        ...        ...        ...        ...       ...   \n","29960      0  ...   208365.0    88004.0    31237.0    15980.0    8500.0   \n","29961      0  ...     3502.0     8979.0     5190.0        0.0    1837.0   \n","29962      0  ...     2758.0    20878.0    20582.0    19357.0       0.0   \n","29963      0  ...    76304.0    52774.0    11855.0    48944.0   85900.0   \n","29964      0  ...    49764.0    36535.0    32428.0    15313.0    2078.0   \n","\n","       PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \n","0         689.0       0.0       0.0       0.0       0.0  \n","1        1000.0    1000.0    1000.0       0.0    2000.0  \n","2        1500.0    1000.0    1000.0    1000.0    5000.0  \n","3        2019.0    1200.0    1100.0    1069.0    1000.0  \n","4       36681.0   10000.0    9000.0     689.0     679.0  \n","...         ...       ...       ...       ...       ...  \n","29960   20000.0    5003.0    3047.0    5000.0    1000.0  \n","29961    3526.0    8998.0     129.0       0.0       0.0  \n","29962       0.0   22000.0    4200.0    2000.0    3100.0  \n","29963    3409.0    1178.0    1926.0   52964.0    1804.0  \n","29964    1800.0    1430.0    1000.0    1000.0    1000.0  \n","\n","[29965 rows x 23 columns]"],"text/html":["\n","  <div id=\"df-1bd4ffbc-86ab-430d-a74a-14d7b9469b43\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        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<td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>34</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>13559.0</td>\n","      <td>14331.0</td>\n","      <td>14948.0</td>\n","      <td>15549.0</td>\n","      <td>1518.0</td>\n","      <td>1500.0</td>\n","      <td>1000.0</td>\n","      <td>1000.0</td>\n","      <td>1000.0</td>\n","      <td>5000.0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>50000.0</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>37</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>49291.0</td>\n","      <td>28314.0</td>\n","      <td>28959.0</td>\n","      <td>29547.0</td>\n","      <td>2000.0</td>\n","      <td>2019.0</td>\n","      <td>1200.0</td>\n","      <td>1100.0</td>\n","      <td>1069.0</td>\n","    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int64"]},"metadata":{},"execution_count":5}]},{"cell_type":"code","source":["crdcd_fd['default.payment.next.month'].value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Griy5m-juW7e","executionInfo":{"status":"ok","timestamp":1694000428868,"user_tz":-330,"elapsed":4,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"daf666c4-7f65-4722-8284-9e7f389abe25"},"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0    23335\n","1     6630\n","Name: default.payment.next.month, dtype: int64"]},"metadata":{},"execution_count":6}]},{"cell_type":"markdown","source":["### SMOTEENN"],"metadata":{"id":"1azxygDv_xLW"}},{"cell_type":"code","source":["import imblearn\n","from imblearn.combine import SMOTEENN as crdcd_fd_smoen\n","from collections import Counter as crdcd_fd_ctt\n","\n","print('stating dataset count %s' % crdcd_fd_ctt(crdcd_fd_o_Y))\n","crdcd_fd_mdl = crdcd_fd_smoen()\n","crdcd_fd_i_X, crdcd_fd_o_Y = crdcd_fd_mdl.fit_resample(crdcd_fd_i_X, crdcd_fd_o_Y)\n","print('After under sampling dataset count %s' % crdcd_fd_ctt(crdcd_fd_o_Y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GmvQFSz1_x16","executionInfo":{"status":"ok","timestamp":1694000686436,"user_tz":-330,"elapsed":19313,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"e7b5b7a3-40dc-4f6c-bd33-ec09cd8ac06a"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["stating dataset count Counter({0: 23335, 1: 6630})\n","After under sampling dataset count Counter({1: 17093, 0: 10298})\n"]}]},{"cell_type":"code","source":["from sklearn.model_selection import train_test_split as crdcd_fdtrrn\n","from sklearn.metrics import classification_report as crdcd_fdclfrt\n","from sklearn.metrics import confusion_matrix as crdcd_fdcfssm\n","from sklearn.metrics import ConfusionMatrixDisplay as crdcd_fdcfxdp\n","from sklearn.model_selection import GridSearchCV as crdcd_fdgshc\n","import warnings as crdcd_fdwin\n","crdcd_fdwin.filterwarnings(\"ignore\")\n","import time as crdcd_fdttee"],"metadata":{"id":"3qXm4ocouqHU","executionInfo":{"status":"ok","timestamp":1694000738935,"user_tz":-330,"elapsed":422,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["# train==60%\n","crdcd_fd_i_Xnt, crdcd_fd_i_Xst, crdcd_fd_o_Ynt, crdcd_fd_o_Yst = crdcd_fdtrrn(crdcd_fd_i_X, crdcd_fd_o_Y, test_size=0.4, random_state=33)"],"metadata":{"id":"t6JPdLy3vijF","executionInfo":{"status":"ok","timestamp":1694000753838,"user_tz":-330,"elapsed":499,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}}},"execution_count":9,"outputs":[]},{"cell_type":"code","source":["# validation==20% & test==20%\n","crdcd_fd_i_Xdv, crdcd_fd_i_Xst, crdcd_fd_o_Ydv, crdcd_fd_o_Yst = crdcd_fdtrrn(crdcd_fd_i_Xst, crdcd_fd_o_Yst, test_size=0.5, random_state=33)"],"metadata":{"id":"7__eWRsuvi5q","executionInfo":{"status":"ok","timestamp":1694000755597,"user_tz":-330,"elapsed":12,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}}},"execution_count":10,"outputs":[]},{"cell_type":"code","source":["print(\"credit card train   : \", crdcd_fd_i_Xnt.shape[0])\n","print(\"credit card validation: \", crdcd_fd_i_Xdv.shape[0])\n","print(\"credit card test : \", crdcd_fd_i_Xst.shape[0])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7O02iTp_vtzA","executionInfo":{"status":"ok","timestamp":1694000767026,"user_tz":-330,"elapsed":421,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"3dd80017-fa56-492f-fd03-6861e7873285"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["credit card train   :  16434\n","credit card validation:  5478\n","credit card test :  5479\n"]}]},{"cell_type":"code","source":["crdcd_fd_i_Xnt"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":443},"id":"pOcF7A5FwvAx","executionInfo":{"status":"ok","timestamp":1694000790511,"user_tz":-330,"elapsed":469,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"26ba9bac-332e-4c3e-978a-4a8bcfe1fc5a"},"execution_count":12,"outputs":[{"output_type":"execute_result","data":{"text/plain":["           LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  \\\n","22954   30000.000000    1          2         2   36     -1     -1     -1   \n","21278  352397.687566    1          1         1   47      0      1      1   \n","22201   90000.000000    1          1         1   44      2      2      2   \n","12545   50000.000000    2          2         1   39      3      3      2   \n","9114    30000.000000    1          2         2   23      1      2      0   \n","...              ...  ...        ...       ...  ...    ...    ...    ...   \n","27282  193455.773319    1          2         1   43      0      0      0   \n","578    180000.000000    2          2         1   28      0      0      0   \n","5848   500000.000000    2          3         1   41      0      0      0   \n","2439   310000.000000    2          2         1   34      0      0     -1   \n","23572   50000.000000    1          2         2   26      0      0      0   \n","\n","       PAY_4  PAY_5  ...      BILL_AMT3      BILL_AMT4      BILL_AMT5  \\\n","22954      0      0  ...     399.224710     399.224710       0.000000   \n","21278      1      1  ...    3163.378095    2213.312801    1645.395858   \n","22201      2      2  ...   79747.529743   80987.406155   82699.842605   \n","12545      0      0  ...   50492.000000   47633.000000   18283.000000   \n","9114       0      0  ...   29235.000000   14040.000000     500.000000   \n","...      ...    ...  ...            ...            ...            ...   \n","27282      0      0  ...  167108.642524  162293.613367  158284.861612   \n","578        0      0  ...   86893.000000   89014.000000   91946.000000   \n","5848       0      0  ...  124836.000000   37334.000000   34944.000000   \n","2439      -1     -1  ...    5565.000000    4050.000000    4922.000000   \n","23572      0      0  ...   30847.062661    9048.349432    8134.656151   \n","\n","           BILL_AMT6     PAY_AMT1      PAY_AMT2     PAY_AMT3      PAY_AMT4  \\\n","22954       0.000000   199.612355    399.224710     0.000000      0.000000   \n","21278    9796.223138  3949.795120   1827.564169  2104.792796    272.856845   \n","22201   84454.140287  3500.000000   3062.793713  3154.264571   3162.793713   \n","12545   18610.000000     0.000000      0.000000  5000.000000   3000.000000   \n","9114    22292.000000     0.000000   1600.000000  1000.000000      0.000000   \n","...              ...          ...           ...          ...           ...   \n","27282  156566.310632  5273.992282   7484.236042  6287.639112   5197.208529   \n","578     93237.000000  5300.000000   4000.000000  4000.000000  10000.000000   \n","5848    24355.000000  7012.000000  10522.000000  6133.000000  24408.000000   \n","2439    15362.000000  1002.000000   5565.000000  4050.000000   4922.000000   \n","23572    8267.098211  1555.439250   1722.280375   652.850469    652.850469   \n","\n","           PAY_AMT5      PAY_AMT6  \n","22954      0.000000      0.000000  \n","21278   9797.661751  10261.291453  \n","22201   3282.941716   4655.004585  \n","12545   1000.000000   2000.000000  \n","9114   22292.000000   1000.000000  \n","...             ...           ...  \n","27282   4788.423490   5253.518697  \n","578     3200.000000   3100.000000  \n","5848     122.000000  17398.000000  \n","2439   15362.000000  12000.000000  \n","23572    542.456918    652.850469  \n","\n","[16434 rows x 23 columns]"],"text/html":["\n","  <div id=\"df-aee708b0-82d3-4087-a9c9-6bee38ff23cb\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>LIMIT_BAL</th>\n","      <th>SEX</th>\n","      <th>EDUCATION</th>\n","      <th>MARRIAGE</th>\n","      <th>AGE</th>\n","      <th>PAY_0</th>\n","      <th>PAY_2</th>\n","      <th>PAY_3</th>\n","      <th>PAY_4</th>\n","      <th>PAY_5</th>\n","      <th>...</th>\n","      <th>BILL_AMT3</th>\n","      <th>BILL_AMT4</th>\n","      <th>BILL_AMT5</th>\n","      <th>BILL_AMT6</th>\n","      <th>PAY_AMT1</th>\n","      <th>PAY_AMT2</th>\n","      <th>PAY_AMT3</th>\n","      <th>PAY_AMT4</th>\n","      <th>PAY_AMT5</th>\n","      <th>PAY_AMT6</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>22954</th>\n","      <td>30000.000000</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>36</td>\n","      <td>-1</td>\n","      <td>-1</td>\n","      <td>-1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>399.224710</td>\n","      <td>399.224710</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>199.612355</td>\n","      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crd_par_bs.best_score_)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"SxrAZnggxGuT","executionInfo":{"status":"ok","timestamp":1694000801851,"user_tz":-330,"elapsed":3109,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"b5d83c9c-11d9-450b-cf62-9902e9197bbe"},"execution_count":15,"outputs":[{"output_type":"stream","name":"stdout","text":["Fitting 2 folds for each of 90 candidates, totalling 180 fits\n","{'criterion': 'gini', 'max_features': 'auto', 'min_samples_leaf': 5, 'splitter': 'best'}\n","credit card-score:  0.736\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_MA= crdcd_fddssn(criterion= 'gini', max_features= 'auto', min_samples_leaf=5 ,splitter='best' )\n","crdcd_fd_MA.fit(crdcd_fd_i_Xnt, crdcd_fd_o_Ynt)\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","print(\"Duration for Training:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jgOwKjWzzmrY","executionInfo":{"status":"ok","timestamp":1694000811480,"user_tz":-330,"elapsed":580,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"76aa6c16-8bae-4d08-c83c-411ae86e6ece"},"execution_count":16,"outputs":[{"output_type":"stream","name":"stdout","text":["Duration for Training: 0.0937042236328125\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MA.predict(crdcd_fd_i_Xdv)\n","print(crdcd_fdclfrt(crdcd_fd_o_Ydv, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Ydv, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for validation:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"STzwfczcqfYx","executionInfo":{"status":"ok","timestamp":1694000814474,"user_tz":-330,"elapsed":27,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"f2a66a87-a0ea-47e5-99c4-3b97efb0f294"},"execution_count":17,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.72      0.74      0.73      2012\n","           1       0.85      0.83      0.84      3466\n","\n","    accuracy                           0.80      5478\n","   macro avg       0.78      0.79      0.79      5478\n","weighted avg       0.80      0.80      0.80      5478\n","\n","Duration for validation: 0.03979825973510742\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MA.predict(crdcd_fd_i_Xst)\n","print(crdcd_fdclfrt(crdcd_fd_o_Yst, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Yst, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for test:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"-Ua6Mcnfzp6Y","executionInfo":{"status":"ok","timestamp":1694000818518,"user_tz":-330,"elapsed":620,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"ff36c91e-3663-4c5c-d55a-d1f880d9a5c8"},"execution_count":18,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.72      0.73      0.73      2048\n","           1       0.84      0.83      0.83      3431\n","\n","    accuracy                           0.79      5479\n","   macro avg       0.78      0.78      0.78      5479\n","weighted avg       0.79      0.79      0.79      5479\n","\n","Duration for test: 0.02472996711730957\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["#### Adaboost classifier"],"metadata":{"id":"u7EFvfYE2DPo"}},{"cell_type":"code","source":["from sklearn.ensemble import AdaBoostClassifier as crdcd_fdadbst\n","\n","crd_par = { 'algorithm':['SAMME','SAMME.R'],\n","              'estimator': ['object',None],\n","               'n_estimators': [50,60,70,80,90],\n","            'learning_rate':[2.0,3.0,4.0,5.0,6.0]}\n","\n","\n","crd_par_bs = crdcd_fdadbst(random_state=33)\n","crd_par_bs = crdcd_fdgshc(crd_par_bs, crd_par, cv=2, verbose=1)\n","crd_par_bs.fit(crdcd_fd_i_Xnt.sample(1000, random_state=33), crdcd_fd_o_Ynt.sample(1000, random_state=33))\n","\n","print( crd_par_bs.best_params_)\n","print(\"credit card-score: \", crd_par_bs.best_score_)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yjGVVmb02Pzk","executionInfo":{"status":"ok","timestamp":1694000846113,"user_tz":-330,"elapsed":22932,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"ce452df2-186d-473a-cf4b-9f90cee52af5"},"execution_count":19,"outputs":[{"output_type":"stream","name":"stdout","text":["Fitting 2 folds for each of 100 candidates, totalling 200 fits\n","{'algorithm': 'SAMME.R', 'estimator': None, 'learning_rate': 4.0, 'n_estimators': 60}\n","credit card-score:  0.6819999999999999\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_MB= crdcd_fdadbst(algorithm= 'SAMME.R', estimator= None, learning_rate=4.0 ,n_estimators=60 )\n","crdcd_fd_MB.fit(crdcd_fd_i_Xnt, crdcd_fd_o_Ynt)\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","print(\"Duration for Training:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yfkj7qsj3AL5","executionInfo":{"status":"ok","timestamp":1694000904947,"user_tz":-330,"elapsed":2615,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"591c2f8a-efe2-481b-b72e-fa62680585bc"},"execution_count":20,"outputs":[{"output_type":"stream","name":"stdout","text":["Duration for Training: 2.2315421104431152\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MB.predict(crdcd_fd_i_Xdv)\n","print(crdcd_fdclfrt(crdcd_fd_o_Ydv, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Ydv, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for validation:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"_sxF2mZ-q9rW","executionInfo":{"status":"ok","timestamp":1694000909072,"user_tz":-330,"elapsed":1236,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"c1427792-f1b7-4a6f-c2c1-cc735ea7a0fc"},"execution_count":21,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.50      0.89      0.64      2012\n","           1       0.89      0.49      0.63      3466\n","\n","    accuracy                           0.64      5478\n","   macro avg       0.69      0.69      0.64      5478\n","weighted avg       0.75      0.64      0.63      5478\n","\n","Duration for validation: 0.1415255069732666\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MB.predict(crdcd_fd_i_Xst)\n","print(crdcd_fdclfrt(crdcd_fd_o_Yst, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Yst, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for test:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"YVCwuMzw3avo","executionInfo":{"status":"ok","timestamp":1694000913075,"user_tz":-330,"elapsed":1099,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"683bd349-cef0-47ce-fbbc-59cfb84e8b3e"},"execution_count":22,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.51      0.89      0.65      2048\n","           1       0.88      0.49      0.63      3431\n","\n","    accuracy                           0.64      5479\n","   macro avg       0.70      0.69      0.64      5479\n","weighted avg       0.74      0.64      0.64      5479\n","\n","Duration for test: 0.10914301872253418\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["#### XGBoost"],"metadata":{"id":"apLku5qH3k0K"}},{"cell_type":"code","source":["from xgboost import XGBClassifier as crdcd_fdxggb\n","\n","crd_par = { 'n_estimators': [10,20,30,40,50],\n","               'learning_rate': [0.1,0.2,0.3,0.4,0.5],\n","            'subsample':[0.2,0.3,0.4,0.5,0.6]}\n","\n","\n","crd_par_bs = crdcd_fdxggb(random_state=33)\n","crd_par_bs = crdcd_fdgshc(crd_par_bs, crd_par, cv=2, verbose=1)\n","crd_par_bs.fit(crdcd_fd_i_Xnt.sample(1000, random_state=33), crdcd_fd_o_Ynt.sample(1000, random_state=33))\n","\n","print( crd_par_bs.best_params_)\n","print(\"credit card-score: \", crd_par_bs.best_score_)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"HOttPa3k4A9W","executionInfo":{"status":"ok","timestamp":1694000930746,"user_tz":-330,"elapsed":14898,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"68c586ca-c5b0-4109-ec50-2b1a715e7f64"},"execution_count":23,"outputs":[{"output_type":"stream","name":"stdout","text":["Fitting 2 folds for each of 125 candidates, totalling 250 fits\n","{'learning_rate': 0.4, 'n_estimators': 50, 'subsample': 0.6}\n","credit card-score:  0.812\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_MC= crdcd_fdxggb(learning_rate= 0.4, n_estimators= 50, subsample=0.6 )\n","crdcd_fd_MC.fit(crdcd_fd_i_Xnt, crdcd_fd_o_Ynt)\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","print(\"Duration for Training:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Ha9zd-d742M3","executionInfo":{"status":"ok","timestamp":1694000954114,"user_tz":-330,"elapsed":3798,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"d74291c4-1821-40a6-cb2a-77e6dec05d49"},"execution_count":24,"outputs":[{"output_type":"stream","name":"stdout","text":["Duration for Training: 4.029340028762817\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MC.predict(crdcd_fd_i_Xdv)\n","print(crdcd_fdclfrt(crdcd_fd_o_Ydv, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Ydv, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for validation:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"RsUqfzeIrOAu","executionInfo":{"status":"ok","timestamp":1694000957536,"user_tz":-330,"elapsed":506,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"c41a7e47-9813-4aeb-cf1b-954e05ae39d6"},"execution_count":25,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.83      0.82      0.82      2012\n","           1       0.90      0.90      0.90      3466\n","\n","    accuracy                           0.87      5478\n","   macro avg       0.86      0.86      0.86      5478\n","weighted avg       0.87      0.87      0.87      5478\n","\n","Duration for validation: 0.03739428520202637\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MC.predict(crdcd_fd_i_Xst)\n","print(crdcd_fdclfrt(crdcd_fd_o_Yst, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Yst, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for test:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"3PijfkLW5Rrd","executionInfo":{"status":"ok","timestamp":1694000964038,"user_tz":-330,"elapsed":1840,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"17246c87-abc0-4e3a-9a4f-66de83071134"},"execution_count":26,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.84      0.81      0.83      2048\n","           1       0.89      0.91      0.90      3431\n","\n","    accuracy                           0.87      5479\n","   macro avg       0.87      0.86      0.86      5479\n","weighted avg       0.87      0.87      0.87      5479\n","\n","Duration for test: 0.17928552627563477\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["#### SVM"],"metadata":{"id":"94zS3uRy5bLo"}},{"cell_type":"code","source":["from sklearn.svm import SVC as crdcd_fdsvv\n","\n","crd_par = { 'kernel':['linear','poly','sigmoid','rbf'],\n","              'gamma': ['scale','auto'],\n","               'tol': [1e-3,1e-4,1e-5,1e-6,1e-7],\n","            'C':[4.0,5.0,6.0,7.0,8.0]}\n","\n","\n","crd_par_bs = crdcd_fdsvv(random_state=33)\n","crd_par_bs = crdcd_fdgshc(crd_par_bs, crd_par, cv=2, verbose=1)\n","crd_par_bs.fit(crdcd_fd_i_Xnt.sample(20, random_state=33), crdcd_fd_o_Ynt.sample(20, random_state=33))\n","\n","print( crd_par_bs.best_params_)\n","print(\"credit card-score: \", crd_par_bs.best_score_)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"oGtRjI6D5fc5","executionInfo":{"status":"ok","timestamp":1694000973056,"user_tz":-330,"elapsed":2388,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"a62fa6aa-9a96-47d4-e818-f370460123b4"},"execution_count":27,"outputs":[{"output_type":"stream","name":"stdout","text":["Fitting 2 folds for each of 200 candidates, totalling 400 fits\n","{'C': 4.0, 'gamma': 'scale', 'kernel': 'sigmoid', 'tol': 0.001}\n","credit card-score:  0.75\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_MD= crdcd_fdsvv(C= 4.0, gamma= 'scale', kernel='sigmoid', tol=0.001 )\n","crdcd_fd_MD.fit(crdcd_fd_i_Xnt.sample(100, random_state=33), crdcd_fd_o_Ynt.sample(100, random_state=33))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","print(\"Duration for Training:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7O9JfvUz6Zci","executionInfo":{"status":"ok","timestamp":1694000984588,"user_tz":-330,"elapsed":10,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"5cb53b60-36f5-4ddb-cf5a-2a761d200df5"},"execution_count":28,"outputs":[{"output_type":"stream","name":"stdout","text":["Duration for Training: 0.008371114730834961\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MD.predict(crdcd_fd_i_Xdv)\n","print(crdcd_fdclfrt(crdcd_fd_o_Ydv, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Ydv, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for validation:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"KT-V6PnlrZvJ","executionInfo":{"status":"ok","timestamp":1694000988665,"user_tz":-330,"elapsed":1480,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"a38a0023-1273-4162-9b80-07cc9b14102e"},"execution_count":29,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.47      0.37      0.41      2012\n","           1       0.68      0.76      0.72      3466\n","\n","    accuracy                           0.62      5478\n","   macro avg       0.58      0.57      0.57      5478\n","weighted avg       0.60      0.62      0.61      5478\n","\n","Duration for validation: 0.11850142478942871\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_MD.predict(crdcd_fd_i_Xst)\n","print(crdcd_fdclfrt(crdcd_fd_o_Yst, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Yst, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for test:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"FB0QN5ty6dYx","executionInfo":{"status":"ok","timestamp":1694000992727,"user_tz":-330,"elapsed":1022,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"2999c524-4bb4-48a1-8a55-c89ca40868d5"},"execution_count":30,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.48      0.34      0.40      2048\n","           1       0.66      0.77      0.72      3431\n","\n","    accuracy                           0.61      5479\n","   macro avg       0.57      0.56      0.56      5479\n","weighted avg       0.59      0.61      0.60      5479\n","\n","Duration for test: 0.03812813758850098\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAgMAAAGwCAYAAAA0bWYRAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABEnklEQVR4nO3deVhUdfs/8PewzAA6M4gGAzoiSqK4a0W0KCaB5mOa9pSphYmaBZqYZlYqaoU/Lbc0rUzRHk1t0RJNRU3RJM1lcucbiqGyuCCMoGwz5/cHcXKC0RlnWM/7dV3ninPO55y5x4uYe+7PcmSCIAggIiIiyXKo6QCIiIioZjEZICIikjgmA0RERBLHZICIiEjimAwQERFJHJMBIiIiiWMyQEREJHFONR2ALYxGIzIyMqBUKiGTyWo6HCIispIgCLh58yZ8fHzg4FB1308LCwtRXFxs833kcjlcXFzsEFHtUqeTgYyMDGi12poOg4iIbHTx4kU0a9asSu5dWFgIP9+GyLpisPleGo0GaWlp9S4hqNPJgFKpBAA8gWfgBOcajoaoauQMf6SmQyCqMobiQpxaO0v8e14ViouLkXXFgL+OtIBKef/VB/1NI3y7XUBxcTGTgdqkvGvACc5wkjEZoPrJUV6//ugQVaY6unobKmVoqLz/1zGi/nZH1+lkgIiIyFIGwQiDDU/jMQhG+wVTyzAZICIiSTBCgBH3nw3Ycm1tx6mFREREEsfKABERSYIRRthS6Lft6tqNyQAREUmCQRBgEO6/1G/LtbUduwmIiIgkjpUBIiKSBA4gNI/JABERSYIRAgxMBirFbgIiIiKJY2WAiIgkgd0E5jEZICIiSeBsAvPYTUBERCRxrAwQEZEkGP/ebLm+vmIyQEREkmCwcTaBLdfWdkwGiIhIEgwCbHxqof1iqW04ZoCIiEjiWBkgIiJJ4JgB85gMEBGRJBghgwEym66vr9hNQEREJHGsDBARkSQYhbLNluvrKyYDREQkCQYbuwlsuba2YzcBERGRxLEyQEREksDKgHlMBoiISBKMggxGwYbZBDZcW9uxm4CIiKgKxMXF4eGHH4ZSqYSnpycGDBiAlJQUkzYhISGQyWQm25gxY0zapKeno2/fvnBzc4OnpycmTZqE0tJSkzZ79uxB165doVAo4O/vj/j4eKtiZTJARESSUN5NYMtmjb179yIqKgq//fYbEhMTUVJSgrCwMBQUFJi0GzVqFDIzM8Vtzpw5/8RsMKBv374oLi7GgQMHsGrVKsTHx2PatGlim7S0NPTt2xc9e/aETqfD+PHjMXLkSGzfvt3iWNlNQEREkmCAAww2fAc2/P1fvV5vclyhUEChUFRov23bNpP9+Ph4eHp64siRI+jevbt43M3NDRqNptLX3LFjB06fPo2dO3fCy8sLnTt3xqxZszB58mTExsZCLpdj2bJl8PPzwyeffAIAaNu2Lfbv34/58+cjPDzcovfGygAREUmC8PeYgfvdhL/HDGi1WqjVanGLi4uz6PXz8vIAAB4eHibH16xZgyZNmqB9+/aYMmUKbt26JZ5LTk5Ghw4d4OXlJR4LDw+HXq/HqVOnxDahoaEm9wwPD0dycrLF/zasDBAREVnh4sWLUKlU4n5lVYF/MxqNGD9+PB5//HG0b99ePD5kyBD4+vrCx8cHx48fx+TJk5GSkoIffvgBAJCVlWWSCAAQ97Oysu7aRq/X4/bt23B1db1nfEwGiIhIEuw1tVClUpkkA5aIiorCyZMnsX//fpPjo0ePFn/u0KEDvL290atXL5w7dw6tWrW671itxW4CIiKSBIPgYPN2P6Kjo5GQkIBffvkFzZo1u2vboKAgAEBqaioAQKPRIDs726RN+X75OANzbVQqlUVVAYDJABERUZUQBAHR0dHYuHEjdu/eDT8/v3teo9PpAADe3t4AgODgYJw4cQJXrlwR2yQmJkKlUiEwMFBss2vXLpP7JCYmIjg42OJY2U1ARESSYIQMRhu+Axth3ZOKoqKisHbtWvz4449QKpViH79arYarqyvOnTuHtWvX4plnnkHjxo1x/PhxxMTEoHv37ujYsSMAICwsDIGBgXj55ZcxZ84cZGVl4f3330dUVJQ4VmHMmDFYvHgx3n77bYwYMQK7d+/Ghg0bsGXLFotjZWWAiIgkobrXGVi6dCny8vIQEhICb29vcVu/fj0AQC6XY+fOnQgLC0ObNm3w1ltvYdCgQdi8ebN4D0dHRyQkJMDR0RHBwcEYNmwYXnnlFcycOVNs4+fnhy1btiAxMRGdOnXCJ598guXLl1s8rRBgZYCIiKhKCMLdKwlarRZ79+695318fX2xdevWu7YJCQnBsWPHrIrvTkwGiIhIEmwZBFh2vXXdBHUJkwEiIpKEsjEDNjyoqB4/tZBjBoiIiCSOlQEiIpIEo43PJrB2NkFdwmSAiIgkgWMGzGMyQEREkmCEQ7WuM1CXcMwAERGRxLEyQEREkmAQZDAINjyoyIZrazsmA0REJAkGGwcQGthNQERERPUVKwNERCQJRsEBRhtmExg5m4CIiKhuYzeBeewmICIikjhWBoiISBKMsG1GgNF+odQ6TAaIiEgSbF90qP4W0+vvOyMiIiKLsDJARESSYPuzCerv92cmA0REJAlGyGCELWMGuAIhERFRncbKgHn1950RERGRRVgZICIiSbB90aH6+/2ZyQAREUmCUZDBaMs6A/X4qYX1N80hIiIii7AyQEREkmC0sZugPi86xGSAiIgkwfanFtbfZKD+vjMiIiKyCCsDREQkCQbIYLBh4SBbrq3tmAwQEZEksJvAvPr7zoiIiMgirAwQEZEkGGBbqd9gv1BqHSYDREQkCewmMI/JABERSQIfVGRe/X1nREREZBFWBoiISBIEyGC0YcyAwKmFREREdRu7Ccyrv++MiIiILMJkgIiIJKH8Eca2bNaIi4vDww8/DKVSCU9PTwwYMAApKSni+ZycHIwdOxYBAQFwdXVF8+bNMW7cOOTl5ZncRyaTVdjWrVtn0mbPnj3o2rUrFAoF/P39ER8fb1WsTAaIiEgSDH8/tdCWzRp79+5FVFQUfvvtNyQmJqKkpARhYWEoKCgAAGRkZCAjIwMff/wxTp48ifj4eGzbtg2RkZEV7rVy5UpkZmaK24ABA8RzaWlp6Nu3L3r27AmdTofx48dj5MiR2L59u8WxcswAERGRFfR6vcm+QqGAQqGo0G7btm0m+/Hx8fD09MSRI0fQvXt3tG/fHt9//714vlWrVvjwww8xbNgwlJaWwsnpn49od3d3aDSaSuNZtmwZ/Pz88MknnwAA2rZti/3792P+/PkIDw+36D2xMkBERJJgr24CrVYLtVotbnFxcRa9fnn538PD465tVCqVSSIAAFFRUWjSpAkeeeQRrFixAoIgiOeSk5MRGhpq0j48PBzJyckWxQWwMkBERBJhhAOMNnwHLr/24sWLUKlU4vHKqgIVrjUaMX78eDz++ONo3759pW2uXbuGWbNmYfTo0SbHZ86ciaeeegpubm7YsWMH3njjDeTn52PcuHEAgKysLHh5eZlc4+XlBb1ej9u3b8PV1fWe8TEZICIisoJKpTJJBiwRFRWFkydPYv/+/ZWe1+v16Nu3LwIDAxEbG2tyburUqeLPXbp0QUFBAebOnSsmA/bAbgIiIpIEgyCzebsf0dHRSEhIwC+//IJmzZpVOH/z5k307t0bSqUSGzduhLOz813vFxQUhEuXLqGoqAgAoNFokJ2dbdImOzsbKpXKoqoAwMoAERFJxP1MD/z39dYQBAFjx47Fxo0bsWfPHvj5+VVoo9frER4eDoVCgZ9++gkuLi73vK9Op0OjRo3E7ong4GBs3brVpE1iYiKCg4MtjpXJABERSYJg41MLBSuvjYqKwtq1a/Hjjz9CqVQiKysLAKBWq+Hq6gq9Xo+wsDDcunUL//vf/6DX68WZCg888AAcHR2xefNmZGdn49FHH4WLiwsSExPx0UcfYeLEieLrjBkzBosXL8bbb7+NESNGYPfu3diwYQO2bNlicaxMBoiIiKrA0qVLAQAhISEmx1euXInhw4fj6NGjOHjwIADA39/fpE1aWhpatGgBZ2dnLFmyBDExMRAEAf7+/pg3bx5GjRoltvXz88OWLVsQExODhQsXolmzZli+fLnF0woBJgNERCQRBshgsOFhQ9Zee+f0v8qEhITcs03v3r3Ru3fve75WSEgIjh07ZlV8d2IyQEREkmAUrO/3//f19RVnExAREUkcKwOEVQdPQ6MtqXD8p/jGWPJuMzgrjBg9PQMhz+bCWSHgyB4lPp3SFLnXyqa/KBuV4p3F6fBrexvKRgbkXXdC8nYVVsZ541a+Y3W/HZK4Lr4ZePnxP9DW+yoeUN3CW9+EY+/Zf0Zxjw75HWHtz8FLnY8SgwPOZDyAz3Y9glOXvSrcy9nRgPhRPyDA+zqGLH0e/5fVBADg7a7H5pi1FdoP//I5nLxU8T5UOxhtHEBoy7W1HZMBwrg+reHg+E/9q0WbQsxefx77NrsDAMbEZuCRUD0+eM0XBXpHRH14GdO+uoAJ/R8EAAhGIHm7CvH/T4O8607w8StC9EeXoXS/hNlRvjXxlkjCXJ1L8WdWY/x0tA0+fqnig1r+uu6OOVufwOUbKiicSjEk+DiWvLIFAxa+hNxbpnOyx4Ul49pNNwR4X6/0tV6P/w/OX/1nadncW/deiY5qjhEyGG0YM2DLtbVdrUhzlixZghYtWsDFxQVBQUE4dOhQTYckKXk5Trhx1VncgkL1yEiT43hyA7gpDQh/KQefx/rgj1+VSD3hhnkTtGj38C206Vr25K38PCckrG6CP4+74cplOXT7ldi8qjHaBxXU8DsjKTqQ2hxLdz+CPWcrzukGgO0nHsSh881w+YYK5696YP72x9DQpRgPepl+4D/mn45HW13Cgh3m52rn3XbB9Xw3cTMYWQmjuqnGk4H169djwoQJmD59Oo4ePYpOnTohPDwcV65cqenQJMnJ2YinBt3A9nUeAGR4sOMtOMsFHNunFNtcTHVB9iVntO12q9J7eHiV4PE+eTie3KCaoia6P06OBjzX7TRu3pbj/7Ibi8c9GtzCe8/uxbQfnkJhifkC6ryXtmHHpHgsH7EJ3QMuVEPEZIuaWoGwLqjxboLy+ZKvvvoqgLJHMW7ZsgUrVqzAO++8U8PRSc9jvfVoqDJgx4ay0qeHZymKi2Qo0Jt+48m96gQPT9NxBu989heCw/Pg4iogeYcK8ydqqy1uIms80fovfPR8IlycS3Et3w1Rq/+DPLGLQMD0537BD4cDcSbDE97u+grX3yp2xvxtwdClayAIMjwVeB4fD96Giet6IymlRbW+F7IcxwyYV6PvrLi4GEeOHDF59KKDgwNCQ0MrffRiUVGRuELTnSs1kf2Ev3Qdv/+iQk723dfGrszn030QHd4a04e3gI9vEV6bnlEFERLZ7nCaD4Ys+y9GfPUcklObI+6FRDRqcBsA8GLQSTSQl2Dlvi5mr8+75Yo1yZ1w6rIXTmd4YvHOR/Hz8dZ4+XFdNb0DIvuq0WTg2rVrMBgMlT56sXzZxjvFxcWZPENaq+U3T3vybFqMLk/mY9vafwZE5VxxglwhoIHKYNLW/YFS5FwxTRhuXHXGxVQX/LZDjYWTm6Hf8OsVqgdEtUFhiTMu5ahx8pIXZv0YAoNRhv5dzwAAHva7jA7abByY+iV+m/Y5No77BgCwevT3iH1ut9l7nrzsCa0Hv6DUZkbIxOcT3NdWjwcQ1ng3gTWmTJmCCRMmiPt6vZ4JgR2FDc5B7jUnHNz5z6M5/zzuhpJiGbo8cRP7t7oDAJq1KoRXsxKcOeJm9l6yv/+fcZbX41U6qN5wkAFyx7KEd+7Pj2Pp7kfEc02UBVjyyha8++3TOHnZ0+w9Wmuu4dpN8/9PUM0TbJxNIDAZqBpNmjSBo6NjpY9e1Gg0FdorFArxKU1kXzKZgLAXc7Dz20YwGv75hb910xHbv/HA6NgM3Mx1QsFNB0R9eBmnD7vh7NGyAYIPP6VHowdKkaJzRWGBI3wDCjFyagZOHnJD9iV5Tb0lkihXeQm0HnniftNGerTWXEPebQXybrlgRPejSEppgWs33eDuVogXHjmJB5QF2HmqFQAgO0+JO/8i3Sou+zN56YYKV/QNAQB9O6Wg1OCAs3+vO/BU2zQ82yUFH/zYo3reJN2X6n5qYV1So8mAXC5Ht27dsGvXLgwYMAAAYDQasWvXLkRHR9dkaJLTpXs+vJqVYPu6xhXOLYv1gVEApn55Ac4KAYf3KLF4SlPxfHGhA/oMvY7XYgvhLBdwNcMZv/6sxvrFXHyFql+gzxV8/upmcX9C77LxR5uPtUZcQne0aJKL/3TeDne3QuTdcsHpDE+MWtHfZL0AS0T2OApv95swGB1w4Zo73v02FLtOt7LreyGqLjLhXk9JqGLr169HREQEPv/8czzyyCNYsGABNmzYgLNnz1YYS/Bver0earUaIegPJ5n1A96I6oLroyx/JjlRXWMoLsTx+PeQl5cHlUp17wvuQ/lnxXOJr8K5wf1XK0sKirHx6ZVVGmtNqfExAy+++CKuXr2KadOmISsrC507d8a2bdvumQgQERFZg90E5tV4MgAA0dHR7BYgIiKqIbUiGSAiIqpqfDaBeUwGiIhIEthNYF79XVuRiIiILMLKABERSQIrA+YxGSAiIklgMmAeuwmIiIgkjpUBIiKSBFYGzGMyQEREkiDAtumB9fmxa0wGiIhIElgZMI9jBoiIiCSOlQEiIpIEVgbMYzJARESSwGTAPHYTEBERSRwrA0REJAmsDJjHZICIiCRBEGQQbPhAt+Xa2o7dBERERBLHygAREUmCETKbFh2y5drajskAERFJAscMmMduAiIiIoljZYCIiCSBAwjNYzJARESSwG4C89hNQEREklBeGbBls0ZcXBwefvhhKJVKeHp6YsCAAUhJSTFpU1hYiKioKDRu3BgNGzbEoEGDkJ2dbdImPT0dffv2hZubGzw9PTFp0iSUlpaatNmzZw+6du0KhUIBf39/xMfHWxUrkwEiIqIqsHfvXkRFReG3335DYmIiSkpKEBYWhoKCArFNTEwMNm/ejG+//RZ79+5FRkYGBg4cKJ43GAzo27cviouLceDAAaxatQrx8fGYNm2a2CYtLQ19+/ZFz549odPpMH78eIwcORLbt2+3OFaZIAh19hHNer0earUaIegPJ5lzTYdDVCWujwqu6RCIqoyhuBDH499DXl4eVCpVlbxG+WdF1+8mwLGB4r7vYygowtHn5913rFevXoWnpyf27t2L7t27Iy8vDw888ADWrl2L559/HgBw9uxZtG3bFsnJyXj00Ufx888/4z//+Q8yMjLg5eUFAFi2bBkmT56Mq1evQi6XY/LkydiyZQtOnjwpvtbgwYORm5uLbdu2WRQbKwNERCQJAgBBsGH7+z56vd5kKyoqsuj18/LyAAAeHh4AgCNHjqCkpAShoaFimzZt2qB58+ZITk4GACQnJ6NDhw5iIgAA4eHh0Ov1OHXqlNjmznuUtym/hyWYDBAREVlBq9VCrVaLW1xc3D2vMRqNGD9+PB5//HG0b98eAJCVlQW5XA53d3eTtl5eXsjKyhLb3JkIlJ8vP3e3Nnq9Hrdv37boPXE2ARERSYIRMsjssALhxYsXTboJFIp7dz1ERUXh5MmT2L9//32/flViMkBERJJgr3UGVCqVVWMGoqOjkZCQgKSkJDRr1kw8rtFoUFxcjNzcXJPqQHZ2NjQajdjm0KFDJvcrn21wZ5t/z0DIzs6GSqWCq6urRTGym4CIiKgKCIKA6OhobNy4Ebt374afn5/J+W7dusHZ2Rm7du0Sj6WkpCA9PR3BwWUDh4ODg3HixAlcuXJFbJOYmAiVSoXAwECxzZ33KG9Tfg9LsDJARESSYBRkkFXjokNRUVFYu3YtfvzxRyiVSrGPX61Ww9XVFWq1GpGRkZgwYQI8PDygUqkwduxYBAcH49FHHwUAhIWFITAwEC+//DLmzJmDrKwsvP/++4iKihK7J8aMGYPFixfj7bffxogRI7B7925s2LABW7ZssThWJgNERCQJ5bMCbLneGkuXLgUAhISEmBxfuXIlhg8fDgCYP38+HBwcMGjQIBQVFSE8PByfffaZ2NbR0REJCQl4/fXXERwcjAYNGiAiIgIzZ84U2/j5+WHLli2IiYnBwoUL0axZMyxfvhzh4eEWx8pkgIiIqApYsoyPi4sLlixZgiVLlpht4+vri61bt971PiEhITh27JjVMZZjMkBERJLABxWZx2SAiIgkgcmAeUwGiIhIEqp7AGFdwqmFREREEsfKABERSUJ1zyaoS5gMEBGRJJQlA7aMGbBjMLUMuwmIiIgkjpUBIiKSBM4mMI/JABERSYLw92bL9fUVuwmIiIgkjpUBIiKSBHYTmMdkgIiIpIH9BGYxGSAiImmwsTKAelwZ4JgBIiIiiWNlgIiIJIErEJrHZICIiCSBAwjNYzcBERGRxLEyQERE0iDIbBsEWI8rA0wGiIhIEjhmwDx2ExAREUkcKwNERCQNXHTILCYDREQkCZxNYJ5FycBPP/1k8Q2fffbZ+w6GiIiIqp9FycCAAQMsuplMJoPBYLAlHiIioqpTj0v9trAoGTAajVUdBxERUZViN4F5Ns0mKCwstFccREREVUuww1ZPWZ0MGAwGzJo1C02bNkXDhg1x/vx5AMDUqVPx1Vdf2T1AIiIiqlpWJwMffvgh4uPjMWfOHMjlcvF4+/btsXz5crsGR0REZD8yO2z1k9XJwOrVq/HFF19g6NChcHR0FI936tQJZ8+etWtwREREdsNuArOsTgYuX74Mf3//CseNRiNKSkrsEhQRERFVH6uTgcDAQOzbt6/C8e+++w5dunSxS1BERER2x8qAWVavQDht2jRERETg8uXLMBqN+OGHH5CSkoLVq1cjISGhKmIkIiKyHZ9aaJbVlYH+/ftj8+bN2LlzJxo0aIBp06bhzJkz2Lx5M55++umqiJGIiIiq0H09m+DJJ59EYmKivWMhIiKqMnyEsXn3/aCiw4cP48yZMwDKxhF069bNbkERERHZHZ9aaJbVycClS5fw0ksv4ddff4W7uzsAIDc3F4899hjWrVuHZs2a2TtGIiIiqkJWjxkYOXIkSkpKcObMGeTk5CAnJwdnzpyB0WjEyJEjqyJGIiIi25UPILRls0JSUhL69esHHx8fyGQybNq0yeS8TCardJs7d67YpkWLFhXOz5492+Q+x48fx5NPPgkXFxdotVrMmTPH6n8aqysDe/fuxYEDBxAQECAeCwgIwKeffoonn3zS6gCIiIiqg0wo22y53hoFBQXo1KkTRowYgYEDB1Y4n5mZabL/888/IzIyEoMGDTI5PnPmTIwaNUrcVyqV4s96vR5hYWEIDQ3FsmXLcOLECYwYMQLu7u4YPXq0xbFanQxotdpKFxcyGAzw8fGx9nZERETVo5rHDPTp0wd9+vQxe16j0Zjs//jjj+jZsydatmxpclypVFZoW27NmjUoLi7GihUrIJfL0a5dO+h0OsybN8+qZMDqboK5c+di7NixOHz4sHjs8OHDePPNN/Hxxx9bezsiIqI6Ra/Xm2xFRUU23zM7OxtbtmxBZGRkhXOzZ89G48aN0aVLF8ydOxelpaXiueTkZHTv3t3kWUHh4eFISUnBjRs3LH59iyoDjRo1gkz2T19JQUEBgoKC4ORUdnlpaSmcnJwwYsQIDBgwwOIXJyIiqjZ2WnRIq9WaHJ4+fTpiY2NtCAxYtWoVlEplhe6EcePGoWvXrvDw8MCBAwcwZcoUZGZmYt68eQCArKws+Pn5mVzj5eUlnmvUqJFFr29RMrBgwQKLbkZERFRr2amb4OLFi1CpVOJhhUJhU1gAsGLFCgwdOhQuLi4mxydMmCD+3LFjR8jlcrz22muIi4uzy+uWsygZiIiIsNsLEhER1WUqlcokGbDVvn37kJKSgvXr19+zbVBQEEpLS3HhwgUEBARAo9EgOzvbpE35vrlxBpWxeszAnQoLCyv0nRAREdVKtfRBRV999RW6deuGTp063bOtTqeDg4MDPD09AQDBwcFISkoyGdifmJiIgIAAi7sIgPtIBgoKChAdHQ1PT080aNAAjRo1MtmIiIhqpWpOBvLz86HT6aDT6QAAaWlp0Ol0SE9PF9vo9Xp8++23la7Tk5ycjAULFuCPP/7A+fPnsWbNGsTExGDYsGHi5+2QIUMgl8sRGRmJU6dOYf369Vi4cKFJ94IlrE4G3n77bezevRtLly6FQqHA8uXLMWPGDPj4+GD16tXW3o6IiKheOnz4MLp06YIuXboAKOv/79KlC6ZNmya2WbduHQRBwEsvvVTheoVCgXXr1qFHjx5o164dPvzwQ8TExOCLL74Q26jVauzYsQNpaWno1q0b3nrrLUybNs2qaYUAIBME6x690Lx5c6xevRohISFQqVQ4evQo/P398fXXX+Obb77B1q1brQrAFnq9Hmq1GiHoDyeZc7W9LlF1uj4quKZDIKoyhuJCHI9/D3l5eXbth79T+WeFdu4HcHB1ufcFZhhvF+LipPerNNaaYnVlICcnR1wQQaVSIScnBwDwxBNPICkpyb7RERER2Un5CoS2bPWV1clAy5YtkZaWBgBo06YNNmzYAADYvHmz+OAiIiIiqjusTgZeffVV/PHHHwCAd955B0uWLIGLiwtiYmIwadIkuwdIRERkF7V0NkFtYPWzCWJiYsSfQ0NDcfbsWRw5cgT+/v7o2LGjXYMjIiKiqmd1MvBvvr6+8PX1tUcsREREVUYGG59aaLdIah+LkoFFixZZfMNx48bddzBERERU/SxKBubPn2/RzWQyWY0kAw7KhnCQye/dkKgOOjxjaU2HQFRl9DeNaBRfTS9mpwcV1UcWJQPlsweIiIjqLDs9qKg+sunZBERERFT32TyAkIiIqE5gZcAsJgNERCQJtq4iyBUIiYiIqN5iZYCIiKSB3QRm3VdlYN++fRg2bBiCg4Nx+fJlAMDXX3+N/fv32zU4IiIiu+FyxGZZnQx8//33CA8Ph6urK44dO4aioiIAQF5eHj766CO7B0hERERVy+pk4IMPPsCyZcvw5ZdfwtnZWTz++OOP4+jRo3YNjoiIyF74CGPzrB4zkJKSgu7du1c4rlarkZuba4+YiIiI7I8rEJpldWVAo9EgNTW1wvH9+/ejZcuWdgmKiIjI7jhmwCyrk4FRo0bhzTffxMGDByGTyZCRkYE1a9Zg4sSJeP3116siRiIiIqpCVncTvPPOOzAajejVqxdu3bqF7t27Q6FQYOLEiRg7dmxVxEhERGQzLjpkntXJgEwmw3vvvYdJkyYhNTUV+fn5CAwMRMOGDasiPiIiIvvgOgNm3feiQ3K5HIGBgfaMhYiIiGqA1clAz549IZOZH1G5e/dumwIiIiKqErZOD2Rl4B+dO3c22S8pKYFOp8PJkycRERFhr7iIiIjsi90EZlmdDMyfP7/S47GxscjPz7c5ICIiIqpedntq4bBhw7BixQp73Y6IiMi+uM6AWXZ7amFycjJcXFzsdTsiIiK74tRC86xOBgYOHGiyLwgCMjMzcfjwYUydOtVugREREVH1sDoZUKvVJvsODg4ICAjAzJkzERYWZrfAiIiIqHpYlQwYDAa8+uqr6NChAxo1alRVMREREdkfZxOYZdUAQkdHR4SFhfHphEREVOfwEcbmWT2boH379jh//nxVxEJEREQ1wOpk4IMPPsDEiRORkJCAzMxM6PV6k42IiKjW4rTCSlk8ZmDmzJl466238MwzzwAAnn32WZNliQVBgEwmg8FgsH+UREREtuKYAbMsTgZmzJiBMWPG4JdffqnKeIiIiKiaWZwMCEJZStSjR48qC4aIiKiqcNEh86yaWni3pxUSERHVauwmMMuqAYStW7eGh4fHXTciIiICkpKS0K9fP/j4+EAmk2HTpk0m54cPHw6ZTGay9e7d26RNTk4Ohg4dCpVKBXd3d0RGRlZ4KODx48fx5JNPwsXFBVqtFnPmzLE6VqsqAzNmzKiwAiEREVFdUN3dBAUFBejUqRNGjBhRYSn/cr1798bKlSvFfYVCYXJ+6NChyMzMRGJiIkpKSvDqq69i9OjRWLt2LQBAr9cjLCwMoaGhWLZsGU6cOIERI0bA3d0do0ePtjhWq5KBwYMHw9PT05pLiIiIagc7dRP8exq9QqGo8CEOAH369EGfPn3uekuFQgGNRlPpuTNnzmDbtm34/fff8dBDDwEAPv30UzzzzDP4+OOP4ePjgzVr1qC4uBgrVqyAXC5Hu3btoNPpMG/ePKuSAYu7CThegIiICNBqtVCr1eIWFxd33/fas2cPPD09ERAQgNdffx3Xr18XzyUnJ8Pd3V1MBAAgNDQUDg4OOHjwoNime/fukMvlYpvw8HCkpKTgxo0bFsdh9WwCIiKiOslOlYGLFy9CpVKJhyurCliid+/eGDhwIPz8/HDu3Dm8++676NOnD5KTk+Ho6IisrKwK1XgnJyd4eHggKysLAJCVlQU/Pz+TNl5eXuI5S58jZHEyYDQaLW1KRERU69hrzIBKpTJJBu7X4MGDxZ87dOiAjh07olWrVtizZw969epl8/2tYfVyxERERHWSLUsRV8OSxC1btkSTJk2QmpoKANBoNLhy5YpJm9LSUuTk5IjjDDQaDbKzs03alO+bG4tQGSYDREREtcClS5dw/fp1eHt7AwCCg4ORm5uLI0eOiG12794No9GIoKAgsU1SUhJKSkrENomJiQgICLC4iwBgMkBERFJRzZWB/Px86HQ66HQ6AEBaWhp0Oh3S09ORn5+PSZMm4bfffsOFCxewa9cu9O/fH/7+/ggPDwcAtG3bFr1798aoUaNw6NAh/Prrr4iOjsbgwYPh4+MDABgyZAjkcjkiIyNx6tQprF+/HgsXLsSECROsitWqqYVERER1VXWvM3D48GH07NlT3C//gI6IiMDSpUtx/PhxrFq1Crm5ufDx8UFYWBhmzZplMiBxzZo1iI6ORq9eveDg4IBBgwZh0aJF4nm1Wo0dO3YgKioK3bp1Q5MmTTBt2jSrphUCTAaIiIiqREhIyF1n4m3fvv2e9/Dw8BAXGDKnY8eO2Ldvn9Xx3YnJABERSQOfTWAWkwEiIpIEPrXQPA4gJCIikjhWBoiISBrYTWAWkwEiIpIGJgNmsZuAiIhI4lgZICIiSZD9vdlyfX3FZICIiKSB3QRmMRkgIiJJ4NRC8zhmgIiISOJYGSAiImlgN4FZTAaIiEg66vEHui3YTUBERCRxrAwQEZEkcACheUwGiIhIGjhmwCx2ExAREUkcKwNERCQJ7CYwj8kAERFJA7sJzGI3ARERkcSxMkBERJLAbgLzmAwQEZE0sJvALCYDREQkDUwGzOKYASIiIoljZYCIiCSBYwbMYzJARETSwG4Cs9hNQEREJHGsDBARkSTIBAEy4f6/3ttybW3HZICIiKSB3QRmsZuAiIhI4lgZICIiSeBsAvOYDBARkTSwm8AsdhMQERFJHCsDREQkCewmMI/JABERSQO7CcxiMkBERJLAyoB5HDNAREQkcUwGiIhIGgQ7bFZISkpCv3794OPjA5lMhk2bNonnSkpKMHnyZHTo0AENGjSAj48PXnnlFWRkZJjco0WLFpDJZCbb7NmzTdocP34cTz75JFxcXKDVajFnzhzrAgWTASIikpDyroL72axVUFCATp06YcmSJRXO3bp1C0ePHsXUqVNx9OhR/PDDD0hJScGzzz5boe3MmTORmZkpbmPHjhXP6fV6hIWFwdfXF0eOHMHcuXMRGxuLL774wqpYOWaAiIjICnq93mRfoVBAoVBUaNenTx/06dOn0nuo1WokJiaaHFu8eDEeeeQRpKeno3nz5uJxpVIJjUZT6X3WrFmD4uJirFixAnK5HO3atYNOp8O8efMwevRoi98TKwNERCQNgmD7BkCr1UKtVotbXFycXcLLy8uDTCaDu7u7yfHZs2ejcePG6NKlC+bOnYvS0lLxXHJyMrp37w65XC4eCw8PR0pKCm7cuGHxa7MyQEREkmCv2QQXL16ESqUSj1dWFbBWYWEhJk+ejJdeesnk3uPGjUPXrl3h4eGBAwcOYMqUKcjMzMS8efMAAFlZWfDz8zO5l5eXl3iuUaNGFr0+kwEiIiIrqFQqkw9sW5WUlOCFF16AIAhYunSpybkJEyaIP3fs2BFyuRyvvfYa4uLi7JKElGM3ARERSUM1zyawRHki8NdffyExMfGeSUZQUBBKS0tx4cIFAIBGo0F2drZJm/J9c+MMKsNkgIiIJEFmtH2zp/JE4M8//8TOnTvRuHHje16j0+ng4OAAT09PAEBwcDCSkpJQUlIitklMTERAQIDFXQQAuwmIiIiqRH5+PlJTU8X9tLQ06HQ6eHh4wNvbG88//zyOHj2KhIQEGAwGZGVlAQA8PDwgl8uRnJyMgwcPomfPnlAqlUhOTkZMTAyGDRsmftAPGTIEM2bMQGRkJCZPnoyTJ09i4cKFmD9/vlWxMhkgxO/6HV7Niioc37zGG9991RSrdh+u9LoP32yD/duawC8gHy+MvoR23fRQNSpF9mUFtq7T4MfVTas6dKIK1n3qiV+3uuNiqgJyFyMCH7qFyPcyoPU3/R0/fdgN8f/PG2ePusHREWjZ7jY+WnsOCteyWvArjwQi+5Lc5JoRUzLw4tgr4v7en9yxbpEXLp9XQN24FM++ehX/feNq1b9Juj/V/GyCw4cPo2fPnuJ+ef9/REQEYmNj8dNPPwEAOnfubHLdL7/8gpCQECgUCqxbtw6xsbEoKiqCn58fYmJiTMYRqNVq7NixA1FRUejWrRuaNGmCadOmWTWtEGAyQADefL4zHBz/+S33ffAW4uJPYt+2xriWqcCQxx8xad/nxSwMiryMw0llmemD7fORm+OMuZMCcDVTgbZd9Rg3MxVGgwyb1/hU63shOp7cEP2GX0PrzrdgKAXiZ3vj3Zda4cu9Z+HiVlbnPX3YDe8NbYXB0dl444PLcHQUcP60K2T/6jh9ZVIm+gy9Lu67NfynTvz7biX+X7Qv3vjgErr1uIn0P12wYJIWchcB/Udcq5b3Stap7mcThISEQBDMX3S3cwDQtWtX/Pbbb/d8nY4dO2Lfvn3WBfcvNZoMJCUlYe7cuThy5AgyMzOxceNGDBgwoCZDkqS8G84m+y+MvoSMv1xw4pAagAw3rpl+O3os9Dr2/dwEhbccAQA7vjcdpJJ1yQVtO9/EY2HXmQxQtfto7XmT/bcWpOPFDh3w53FXdHi0AADweWxTDIi8avIt/9+VAwBwbWiEh2dpheMAsPM7DzzWOw//eaUsWfD2Lcbg6GxsWOKJZ1+9BpnMXu+I7OaOtQLu+/p6qkYHEN5tqUaqGU7ORvR89gp2fO8FoOJfM/92+WgVWIDt33nd9T4NlKXIz2XhiWpegb4saVW6GwAAudeccPZoA7g3LsX4fg/ixY7tMHGgP04ebFDh2g2LPfF8u/Z44+nW+PazB2C4Iy8oKZZBrjAdUSZ3MeJaprxC9wJRbVejf63vtlRjZYqKilBU9E/2/u8lIcl2waHX0VBZisSNnpWeD38+C+mprjhzzPz0l7Zd9Oje5xqmvxZYVWESWcRoBJZNb4p2D+ejRZtCAEDmX2Uf1F/P02DU1Ay0ancbO79rhHdebIXPd59F05bFAID+kVfh3+E2lO6lOH24AVbGeSPnijNeiy17kMxDITexbLoPnn6hITo9no+MNAW+/7zs/5ucbCdotMU18I7pbvgIY/Pq1Fe3uLg4zJgxo6bDqNfCB2XjcFIj5FypuJiFXGFAyH+u4pvPtGav932wANM/O401S7Q4+qvl01qIqsLid5vhr7Ou+GTTn+Ix499f5p8Zdh3hg3MAAP4dbkO3X4nt6xpjxLuZAIBBr/0zELBlYCGcnQUsnKzFq1MyIVcI6DP0OjIuyDEtoiVKS2RwUxrwXORVfP2JNxw4abt2quYBhHVJnfqVnTJlCvLy8sTt4sWLNR1SveLpU4jOj+Vi23eVL1TxRO/rULgYsWtT5V0EzVuVDTz8eb0G65Y2r7QNUXVZ/G5THExUYc53qXjA55852I29ymr9vq0LTdpr/Qtx5bLp+Jk7BXS9BUOpDNkXyyoLMhkw8v1MbPrzOL4+dBrrdKcQ0OUWAEDjW3H8AVFtVqcqA+aeDEX28fTAbORdd8ahPR6Vng8flIWDuz0qDDgEgOb+BZi96iR2bvLEqgUtqjhSIvMEAVjyXlMc2KbG3O9SoWluWq730hajsaYYl86Z/i25fF6Bh566afa+50+5wsFBgHsT0wGFjo5AE++yZOOXTY3QtlsB3Bsb7PRuyJ7YTWBenUoGqOrIZAKeHngFOzd5wWioOHDQu/lttH9Yj2mj21U45/tgWSJwZL87Nq5sikZNyv74Gg2yShMHoqq0+N1m+GVjI8SuPA/XhkbkXCn7M9dAaYDCVYBMBjz/+lV8/bEGLQNvo2W729j5rQcunnPB+19eAFA29fDssQbo9NhNuDU04syRBlg23QdPDbohDkTMu+6IfVvc0TE4HyVFDtix3gP7Etwx9/tUc6FRTeNsArOYDBAAoMtjufBqWvT3LIKKwgZl41qWAkf3u1c490T4Nbg3LkGv/lfRq/8//azZlxQY3uvhqgqZqFIJq5oAACYNetDk+Fvz0xH2YtkYgYGjrqKkUIZl05viZq4jWgYWIu6bc/BpUZbIOssF7P3RHf/7RIOSYhk02mIMHH0VA0ebLii081sPfDnTB4IAtO12C3O/S0Wbv7sKiOoSmXCvVQ+q0J1LNXbp0gXz5s1Dz5494eHhgebN793nrNfroVar8ZRyKJxknMpD9dPPKbYtJkJUm+lvGtGo9Xnk5eXZ9UmAJq/x92dFcJ+ZcHJ2ue/7lJYUIvnnaVUaa02p0crA3ZZqjI+Pr6GoiIioXuJsArNqNBm411KNREREVPU4ZoCIiCSBswnMYzJARETSYBTKNluur6eYDBARkTRwzIBZdWoFQiIiIrI/VgaIiEgSZLBxzIDdIql9mAwQEZE0cAVCs9hNQEREJHGsDBARkSRwaqF5TAaIiEgaOJvALHYTEBERSRwrA0REJAkyQYDMhkGAtlxb2zEZICIiaTD+vdlyfT3FbgIiIiKJY2WAiIgkgd0E5jEZICIiaeBsArOYDBARkTRwBUKzOGaAiIhI4lgZICIiSeAKhOYxGSAiImlgN4FZ7CYgIiKSOFYGiIhIEmTGss2W6+srJgNERCQN7CYwi90EREREEsfKABERSQMXHTKLyQAREUkClyM2j90EREREVSApKQn9+vWDj48PZDIZNm3aZHJeEARMmzYN3t7ecHV1RWhoKP7880+TNjk5ORg6dChUKhXc3d0RGRmJ/Px8kzbHjx/Hk08+CRcXF2i1WsyZM8fqWJkMEBGRNJQPILRls0JBQQE6deqEJUuWVHp+zpw5WLRoEZYtW4aDBw+iQYMGCA8PR2Fhodhm6NChOHXqFBITE5GQkICkpCSMHj1aPK/X6xEWFgZfX18cOXIEc+fORWxsLL744gurYmU3ARERSYMAwJbpgVb2EvTp0wd9+vSp/FaCgAULFuD9999H//79AQCrV6+Gl5cXNm3ahMGDB+PMmTPYtm0bfv/9dzz00EMAgE8//RTPPPMMPv74Y/j4+GDNmjUoLi7GihUrIJfL0a5dO+h0OsybN88kabgXVgaIiEgSyscM2LIBZd/G79yKioqsjiUtLQ1ZWVkIDQ0Vj6nVagQFBSE5ORkAkJycDHd3dzERAIDQ0FA4ODjg4MGDYpvu3btDLpeLbcLDw5GSkoIbN25YHA+TASIiIitotVqo1Wpxi4uLs/oeWVlZAAAvLy+T415eXuK5rKwseHp6mpx3cnKCh4eHSZvK7nHna1iC3QRERCQNAmxcdKjsPxcvXoRKpRIPKxQK2+KqBVgZICIiabDTAEKVSmWy3U8yoNFoAADZ2dkmx7Ozs8VzGo0GV65cMTlfWlqKnJwckzaV3ePO17AEkwEiIqJq5ufnB41Gg127donH9Ho9Dh48iODgYABAcHAwcnNzceTIEbHN7t27YTQaERQUJLZJSkpCSUmJ2CYxMREBAQFo1KiRxfEwGSAiImkw2mGzQn5+PnQ6HXQ6HYCyQYM6nQ7p6emQyWQYP348PvjgA/z00084ceIEXnnlFfj4+GDAgAEAgLZt26J3794YNWoUDh06hF9//RXR0dEYPHgwfHx8AABDhgyBXC5HZGQkTp06hfXr12PhwoWYMGGCVbFyzAAREUlCda9AePjwYfTs2VPcL/+AjoiIQHx8PN5++20UFBRg9OjRyM3NxRNPPIFt27bBxcVFvGbNmjWIjo5Gr1694ODggEGDBmHRokXiebVajR07diAqKgrdunVDkyZNMG3aNKumFf793uru+op6vR5qtRpPKYfCSSa/9wVEddDPKftqOgSiKqO/aUSj1ueRl5dnMijPrq/x92dFr/Zvw8nx/gf7lRqKsOvknCqNtaawMkBERNLARxibxWSAiIikgcmAWRxASEREJHGsDBARkTSwMmAWkwEiIpIGIwCZjdfXU0wGiIhIEqp7amFdwjEDREREEsfKABERSQPHDJjFZICIiKTBKAAyGz7QjfU3GWA3ARERkcSxMkBERNLAbgKzmAwQEZFE2JgMoP4mA+wmICIikjhWBoiISBrYTWAWkwEiIpIGowCbSv2cTUBERET1FSsDREQkDYKxbLPl+nqKyQAREUkDxwyYxWSAiIikgWMGzOKYASIiIoljZYCIiKSB3QRmMRkgIiJpEGBjMmC3SGoddhMQERFJHCsDREQkDewmMIvJABERSYPRCMCGtQKM9XedAXYTEBERSRwrA0REJA3sJjCLyQAREUkDkwGz2E1AREQkcawMEBGRNHA5YrOYDBARkSQIghGCDU8etOXa2o7JABERSYMg2PbtnmMGiIiIqL5iZYCIiKRBsHHMQD2uDDAZICIiaTAaAZkN/f71eMwAuwmIiIgkjskAERFJQ/miQ7ZsVmjRogVkMlmFLSoqCgAQEhJS4dyYMWNM7pGeno6+ffvCzc0Nnp6emDRpEkpLS+32T1KO3QRERCQJgtEIwYZuAmunFv7+++8wGAzi/smTJ/H000/jv//9r3hs1KhRmDlzprjv5uYm/mwwGNC3b19oNBocOHAAmZmZeOWVV+Ds7IyPPvrovt9HZZgMEBERVYEHHnjAZH/27Nlo1aoVevToIR5zc3ODRqOp9PodO3bg9OnT2LlzJ7y8vNC5c2fMmjULkydPRmxsLORyud1iZTcBERFJg526CfR6vclWVFR0z5cuLi7G//73P4wYMQIymUw8vmbNGjRp0gTt27fHlClTcOvWLfFccnIyOnToAC8vL/FYeHg49Ho9Tp06Zcd/GFYGiIhIKowCILN9aqFWqzU5PH36dMTGxt710k2bNiE3NxfDhw8Xjw0ZMgS+vr7w8fHB8ePHMXnyZKSkpOCHH34AAGRlZZkkAgDE/aysrPt/H5VgMkBERGSFixcvQqVSifsKheKe13z11Vfo06cPfHx8xGOjR48Wf+7QoQO8vb3Rq1cvnDt3Dq1atbJv0PfAZICIiKRBEADYss5AWWVApVKZJAP38tdff2Hnzp3iN35zgoKCAACpqalo1aoVNBoNDh06ZNImOzsbAMyOM7hfHDNARESSIBgFm7f7sXLlSnh6eqJv3753bafT6QAA3t7eAIDg4GCcOHECV65cEdskJiZCpVIhMDDwvmIxh5UBIiKSBsEI2yoD1l9rNBqxcuVKREREwMnpn4/cc+fOYe3atXjmmWfQuHFjHD9+HDExMejevTs6duwIAAgLC0NgYCBefvllzJkzB1lZWXj//fcRFRVlUdeENZgMEBERVZGdO3ciPT0dI0aMMDkul8uxc+dOLFiwAAUFBdBqtRg0aBDef/99sY2joyMSEhLw+uuvIzg4GA0aNEBERITJugT2wmSAiIgkQTAKEGyYTSDcx4OKwsLCKr1Oq9Vi796997ze19cXW7dutfp1rcVkgIiIpKEGugnqijqdDJRnW6VCSQ1HQlR19Dfr7x8gIn1+2e/3/XzrtlYpSmx6gnEp6u9nTZ1OBm7evAkASMrfUMOREFWdRq1rOgKiqnfz5k2o1eoqubdcLodGo8H+LNvL7RqNxq7LANcWMqE60rEqYjQakZGRAaVSabK8I1UdvV4PrVZbYdENovqAv9/VTxAE3Lx5Ez4+PnBwqLrZ7oWFhSguLrb5PnK5HC4uLnaIqHap05UBBwcHNGvWrKbDkCRrF90gqkv4+129qqoicCcXF5d6+SFuL1x0iIiISOKYDBAREUkckwGyikKhwPTp0+2++hVRbcDfb5KqOj2AkIiIiGzHygAREZHEMRkgIiKSOCYDREREEsdkgIiISOKYDJDFlixZghYtWsDFxQVBQUE4dOhQTYdEZBdJSUno168ffHx8IJPJsGnTppoOiahaMRkgi6xfvx4TJkzA9OnTcfToUXTq1Anh4eG4cuVKTYdGZLOCggJ06tQJS5YsqelQiGoEpxaSRYKCgvDwww9j8eLFAMqeC6HVajF27Fi88847NRwdkf3IZDJs3LgRAwYMqOlQiKoNKwN0T8XFxThy5AhCQ0PFYw4ODggNDUVycnINRkZERPbAZIDu6dq1azAYDPDy8jI57uXlhaysrBqKioiI7IXJABERkcQxGaB7atKkCRwdHZGdnW1yPDs7GxqNpoaiIiIie2EyQPckl8vRrVs37Nq1SzxmNBqxa9cuBAcH12BkRERkD041HQDVDRMmTEBERAQeeughPPLII1iwYAEKCgrw6quv1nRoRDbLz89HamqquJ+WlgadTgcPDw80b968BiMjqh6cWkgWW7x4MebOnYusrCx07twZixYtQlBQUE2HRWSzPXv2oGfPnhWOR0REID4+vvoDIqpmTAaIiIgkjmMGiIiIJI7JABERkcQxGSAiIpI4JgNEREQSx2SAiIhI4pgMEBERSRyTASIiIoljMkBERCRxTAaIbDR8+HAMGDBA3A8JCcH48eOrPY49e/ZAJpMhNzfXbBuZTIZNmzZZfM/Y2Fh07tzZprguXLgAmUwGnU5n032IqOowGaB6afjw4ZDJZJDJZJDL5fD398fMmTNRWlpa5a/9ww8/YNasWRa1teQDnIioqvFBRVRv9e7dGytXrkRRURG2bt2KqKgoODs7Y8qUKRXaFhcXQy6X2+V1PTw87HIfIqLqwsoA1VsKhQIajQa+vr54/fXXERoaip9++gnAP6X9Dz/8ED4+PggICAAAXLx4ES+88ALc3d3h4eGB/v3748KFC+I9DQYDJkyYAHd3dzRu3Bhvv/02/v14j393ExQVFWHy5MnQarVQKBTw9/fHV199hQsXLogPx2nUqBFkMhmGDx8OoOwR0XFxcfDz84Orqys6deqE7777zuR1tm7ditatW8PV1RU9e/Y0idNSkydPRuvWreHm5oaWLVti6tSpKCkpqdDu888/h1arhZubG1544QXk5eWZnF++fDnatm0LFxcXtGnTBp999pnVsRBRzWEyQJLh6uqK4uJicX/Xrl1ISUlBYmIiEhISUFJSgvDwcCiVSuzbtw+//vorGjZsiN69e4vXffLJJ4iPj8eKFSuwf/9+5OTkYOPGjXd93VdeeQXffPMNFi1ahDNnzuDzzz9Hw4YNodVq8f333wMAUlJSkJmZiYULFwIA4uLisHr1aixbtgynTp1CTEwMhg0bhr179wIoS1oGDhyIfv36QafTYeTIkXjnnXes/jdRKpWIj4/H6dOnsXDhQnz55ZeYP3++SZvU1FRs2LABmzdvxrZt23Ds2DG88cYb4vk1a9Zg2rRp+PDDD3HmzBl89NFHmDp1KlatWmV1PERUQwSieigiIkLo37+/IAiCYDQahcTEREGhUAgTJ04Uz3t5eQlFRUXiNV9//bUQEBAgGI1G8VhRUZHg6uoqbN++XRAEQfD29hbmzJkjni8pKRGaNWsmvpYgCEKPHj2EN998UxAEQUhJSREACImJiZXG+csvvwgAhBs3bojHCgsLBTc3N+HAgQMmbSMjI4WXXnpJEARBmDJlihAYGGhyfvLkyRXu9W8AhI0bN5o9P3fuXKFbt27i/vTp0wVHR0fh0qVL4rGff/5ZcHBwEDIzMwVBEIRWrVoJa9euNbnPrFmzhODgYEEQBCEtLU0AIBw7dszs6xJRzeKYAaq3EhIS0LBhQ5SUlMBoNGLIkCGIjY0Vz3fo0MFknMAff/yB1NRUKJVKk/sUFhbi3LlzyMvLQ2ZmJoKCgsRzTk5OeOihhyp0FZTT6XRwdHREjx49LI47NTUVt27dwtNPP21yvLi4GF26dAEAnDlzxiQOAAgODrb4NcqtX78eixYtwrlz55Cfn4/S0lKoVCqTNs2bN0fTpk1NXsdoNCIlJQVKpRLnzp1DZGQkRo0aJbYpLS2FWq22Oh4iqhlMBqje6tmzJ5YuXQq5XA4fHx84OZn+ujdo0MBkPz8/H926dcOaNWsq3OuBBx64rxhcXV2tviY/Px8AsGXLFpMPYaBsHIS9JCcnY+jQoZgxYwbCw8OhVquxbt06fPLJJ1bH+uWXX1ZIThwdHe0WKxFVLSYDVG81aNAA/v7+Frfv2rUr1q9fD09Pzwrfjst5e3vj4MGD6N69O4Cyb8BHjhxB165dK23foUMHGI1G7N27F6GhoRXOl1cmDAaDeCwwMBAKhQLp6elmKwpt27YVB0OW++233+79Ju9w4MAB+Pr64r333hOP/fXXXxXapaenIyMjAz4+PuLrODg4ICAgAF5eXvDx8cH58+cxdOhQq16fiGoPDiAk+tvQoUPRpEkT9O/fH/v27UNaWhr27NmDcePG4dKlSwCAN998E7Nnz8amTZtw9uxZvPHGG3ddI6BFixaIiIjAiBEjsGnTJvGeGzZsAAD4+vpCJpMhISEBV69eRX5+PpRKJSZOnIiYmBisWrUK586dw9GjR/Hpp5+Kg/LGjBmDP//8E5MmTUJKSgrWrl2L+Ph4q97vgw8+iPT0dKxbtw7nzp3DokWLKh0M6eLigoiICPzxxx/Yt28fxo0bhxdeeAEajQYAMGPGDMTFxWHRokX4v//7P5w4cQIrV67EvHnzrIqHiGoOkwGiv7m5uSEpKQnNmzfHwIED0bZtW0RGRqKwsFCsFLz11lt4+eWXERERgeDgYCiVSjz33HN3ve/SpUvx/PPP44033kCbNm0watQoFBQUAACaNm2KGTNm4J133oGXlxeio6MBALNmzcLUqVMRFxeHtm3bonfv3tiyZQv8/PwAlPXjf//999i0aRM6deqEZcuW4aOPPrLq/T777LOIiYlBdHQ0OnfujAMHDmDq1KkV2vn7+2PgwIF45plnEBYWho4dO5pMHRw5ciSWL1+OlStXokOHDujRowfi4+PFWImo9pMJ5kY+ERERkSSwMkBERCRxTAaIiIgkjskAERGRxDEZICIikjgmA0RERBLHZICIiEjimAwQERFJHJMBIiIiiWMyQEREJHFMBoiIiCSOyQAREZHE/X9X7tlTWxn1jQAAAABJRU5ErkJggg==\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### DL algorithm-credit card fraud detection"],"metadata":{"id":"XfVJnod06pZe"}},{"cell_type":"markdown","source":["#### MLP"],"metadata":{"id":"rwPwUP096z_b"}},{"cell_type":"code","source":["from sklearn.neural_network import MLPClassifier as crdcd_fdmmllp\n","\n","crd_par = {'activation':['identity','tanh','relu','logistic'],\n","              'solver': ['adam','lbfgs'],\n","               'learning_rate': ['constant','invscaling','adaptive'],\n","            'hidden_layer_sizes':[(100,), (150,), (200,),(300,)],\n","           'alpha':[0.1, 0.001, 0.01]}\n","\n","\n","crd_par_bs = crdcd_fdmmllp(random_state=33)\n","crd_par_bs = crdcd_fdgshc(crd_par_bs, crd_par, cv=2, verbose=1)\n","crd_par_bs.fit(crdcd_fd_i_Xnt.sample(10, random_state=33), crdcd_fd_o_Ynt.sample(10, random_state=33))\n","\n","print( crd_par_bs.best_params_)\n","print(\"credit card-score: \", crd_par_bs.best_score_)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"sV5YAOdS619T","executionInfo":{"status":"ok","timestamp":1694001050930,"user_tz":-330,"elapsed":54470,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"09eef005-3615-4732-fd80-d049d5a59c07"},"execution_count":31,"outputs":[{"output_type":"stream","name":"stdout","text":["Fitting 2 folds for each of 288 candidates, totalling 576 fits\n","{'activation': 'identity', 'alpha': 0.1, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'solver': 'adam'}\n","credit card-score:  0.9\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_ME= crdcd_fdmmllp(activation= 'identity', learning_rate= 'constant',solver='adam',hidden_layer_sizes=(100,),alpha=0.1 )\n","crdcd_fd_ME.fit(crdcd_fd_i_Xnt, crdcd_fd_o_Ynt)\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","print(\"Duration for Training:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bxW6eWuO7wO5","executionInfo":{"status":"ok","timestamp":1694001088056,"user_tz":-330,"elapsed":10284,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"dd6681dc-6052-4ce9-e0cd-5dc9792dc34e"},"execution_count":32,"outputs":[{"output_type":"stream","name":"stdout","text":["Duration for Training: 10.017461061477661\n"]}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_ME.predict(crdcd_fd_i_Xdv)\n","print(crdcd_fdclfrt(crdcd_fd_o_Ydv, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Ydv, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for validation:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"JjijY51SrqDA","executionInfo":{"status":"ok","timestamp":1694001125653,"user_tz":-330,"elapsed":569,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"fd3dd762-1938-495a-f71b-dc51bf374c91"},"execution_count":33,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.79      0.22      0.35      2012\n","           1       0.68      0.97      0.80      3466\n","\n","    accuracy                           0.69      5478\n","   macro avg       0.74      0.59      0.57      5478\n","weighted avg       0.72      0.69      0.63      5478\n","\n","Duration for validation: 0.04038882255554199\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["crdcd_pt1 = crdcd_fdttee.time()\n","\n","crdcd_fd_Pp= crdcd_fd_ME.predict(crdcd_fd_i_Xst)\n","print(crdcd_fdclfrt(crdcd_fd_o_Yst, crdcd_fd_Pp))\n","\n","crdcd_pt2 = crdcd_fdttee.time()\n","crdcd_rdo = crdcd_fdcfssm(crdcd_fd_o_Yst, crdcd_fd_Pp)\n","crdcd_rex = crdcd_fdcfxdp(confusion_matrix = crdcd_rdo, display_labels = [0, 1])\n","crdcd_rex.plot()\n","print(\"Duration for test:\", crdcd_pt2-crdcd_pt1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":623},"id":"866s0vwu7wQa","executionInfo":{"status":"ok","timestamp":1694001131204,"user_tz":-330,"elapsed":866,"user":{"displayName":"Jadaprojects05","userId":"10289941972047474523"}},"outputId":"ef0a137e-e6fc-4c82-ae8c-3f15309ba0c4"},"execution_count":34,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.79      0.22      0.34      2048\n","           1       0.67      0.97      0.79      3431\n","\n","    accuracy                           0.69      5479\n","   macro avg       0.73      0.59      0.57      5479\n","weighted avg       0.72      0.69      0.62      5479\n","\n","Duration for test: 0.04143786430358887\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["*** XGBoost has highest accuracy (87%)"],"metadata":{"id":"7Dogn1soRrUn"}}]}