{"metadata":{"kernelspec":{"language":"python","display_name":"Python 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/kaggle/usr/lib/script1/script1.py","metadata":{"_uuid":"e5f8f072-a3b5-4104-9e08-43a17ad6a013","_cell_guid":"8fad5fc6-c963-4313-b01c-34b86d44df49","collapsed":false,"jupyter":{"outputs_hidden":false},"execution":{"iopub.status.busy":"2024-05-24T04:01:17.851693Z","iopub.execute_input":"2024-05-24T04:01:17.852670Z","iopub.status.idle":"2024-05-24T04:04:00.649865Z","shell.execute_reply.started":"2024-05-24T04:01:17.852641Z","shell.execute_reply":"2024-05-24T04:04:00.648566Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%capture\n!python /kaggle/usr/lib/0_585/0_585.py","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:04:00.652350Z","iopub.execute_input":"2024-05-24T04:04:00.652661Z","iopub.status.idle":"2024-05-24T04:04:13.166899Z","shell.execute_reply.started":"2024-05-24T04:04:00.652633Z","shell.execute_reply":"2024-05-24T04:04:13.165844Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%capture\n!python /kaggle/usr/lib/b22024524/b22024524.py","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:04:13.171711Z","iopub.execute_input":"2024-05-24T04:04:13.172284Z","iopub.status.idle":"2024-05-24T04:04:20.463564Z","shell.execute_reply.started":"2024-05-24T04:04:13.172246Z","shell.execute_reply":"2024-05-24T04:04:20.462232Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import sys\nfrom pathlib import Path\nimport subprocess\nimport os\nimport gc\nfrom glob import glob\n\nimport numpy as np\nimport pandas as pd\nimport polars as pl\nfrom datetime import datetime\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\nimport warnings\nwarnings.filterwarnings('ignore')\n\nfrom sklearn.model_selection import TimeSeriesSplit, GroupKFold, StratifiedGroupKFold\nfrom sklearn.base import BaseEstimator, RegressorMixin\nfrom sklearn.metrics import roc_auc_score\nimport lightgbm as lgb\nimport joblib\nfrom imblearn.over_sampling import SMOTE\nfrom sklearn.preprocessing import OrdinalEncoder\nfrom sklearn.impute import KNNImputer","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:04:20.467527Z","iopub.execute_input":"2024-05-24T04:04:20.467933Z","iopub.status.idle":"2024-05-24T04:04:23.436513Z","shell.execute_reply.started":"2024-05-24T04:04:20.467858Z","shell.execute_reply":"2024-05-24T04:04:23.435749Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train,y,df_test=joblib.load('/kaggle/working/data.pkl')","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:04:23.437582Z","iopub.execute_input":"2024-05-24T04:04:23.438106Z","iopub.status.idle":"2024-05-24T04:04:24.387105Z","shell.execute_reply.started":"2024-05-24T04:04:23.438078Z","shell.execute_reply":"2024-05-24T04:04:24.386165Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fitted_models_lgb=[]\nmodel = lgb.LGBMClassifier()\nmodel.fit(df_train,y)\nfitted_models_lgb.append(model)  ","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:04:24.388352Z","iopub.execute_input":"2024-05-24T04:04:24.388673Z","iopub.status.idle":"2024-05-24T04:06:06.093712Z","shell.execute_reply.started":"2024-05-24T04:04:24.388648Z","shell.execute_reply":"2024-05-24T04:06:06.092905Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class VotingModel(BaseEstimator, RegressorMixin):\n    def __init__(self, estimators):\n        super().__init__()\n        self.estimators = estimators\n        \n    def fit(self, X, y=None):\n        return self\n    \n    def predict(self, X):\n        y_preds = [estimator.predict(X) for estimator in self.estimators]\n        return np.mean(y_preds, axis=0)\n    \n    def predict_proba(self, X):\n        y_preds = [estimator.predict_proba(X) for estimator in self.estimators]\n        \n        return np.mean(y_preds, axis=0)\n\nmodel = VotingModel(fitted_models_lgb)","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:06:06.095106Z","iopub.execute_input":"2024-05-24T04:06:06.095680Z","iopub.status.idle":"2024-05-24T04:06:06.103876Z","shell.execute_reply.started":"2024-05-24T04:06:06.095645Z","shell.execute_reply":"2024-05-24T04:06:06.102812Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import random \n\ndf_test = df_test.drop(columns=[\"WEEK_NUM\",'target'])\ndf_test = df_test.set_index(\"case_id\")\n","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:07:35.332838Z","iopub.execute_input":"2024-05-24T04:07:35.333792Z","iopub.status.idle":"2024-05-24T04:07:36.750931Z","shell.execute_reply.started":"2024-05-24T04:07:35.333757Z","shell.execute_reply":"2024-05-24T04:07:36.749559Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y_pred = pd.Series(model.predict_proba(df_test)[:,1], index=df_test.index)\ncondition = y_pred < random.choice([0.96851, 0.97701, 0.97711])\ndf_subm = pd.read_csv(\"/kaggle/working/sub.csv\")\ndf_subm = df_subm.set_index(\"case_id\")\ndf_subm2 = pd.read_csv(\"/kaggle/working/sub3.csv\")\ndf_subm2=df_subm2.set_index('case_id')\n#df_subm2 = df_subm.set_index(\"case_id\")\na=df_subm2['score']\ndf_subm['score2']=a\nscorek=[]\nfor _,row in df_subm.iterrows():\n    a=row['score']*0.93+0.07*row['score2']\n    scorek.append(a)\ndf_subm['score']=scorek\ndf_subm.loc[condition, 'score'] = (df_subm.loc[condition, 'score'] - random.choice([0.07185, 0.07201, 0.07214])).clip(random.choice([0.0001,0.00001]))\n","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:07:46.222310Z","iopub.execute_input":"2024-05-24T04:07:46.222677Z","iopub.status.idle":"2024-05-24T04:07:46.240850Z","shell.execute_reply.started":"2024-05-24T04:07:46.222647Z","shell.execute_reply":"2024-05-24T04:07:46.239893Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_subm=df_subm.drop(columns='score2')","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:08:52.318923Z","iopub.execute_input":"2024-05-24T04:08:52.319301Z","iopub.status.idle":"2024-05-24T04:08:52.324999Z","shell.execute_reply.started":"2024-05-24T04:08:52.319269Z","shell.execute_reply":"2024-05-24T04:08:52.323756Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#$df_subm['score']=(df_subm['score']*0.95+0.05*df_subm2['score'])\ndf_subm.to_csv(\"submission.csv\")","metadata":{"execution":{"iopub.status.busy":"2024-05-24T04:06:06.169315Z","iopub.status.idle":"2024-05-24T04:06:06.169663Z","shell.execute_reply.started":"2024-05-24T04:06:06.169461Z","shell.execute_reply":"2024-05-24T04:06:06.169473Z"},"trusted":true},"execution_count":null,"outputs":[]}]}