{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":84896,"databundleVersionId":10305135,"sourceType":"competition"},{"sourceId":10299542,"sourceType":"datasetVersion","datasetId":6374977},{"sourceId":10319506,"sourceType":"datasetVersion","datasetId":6389029},{"sourceId":10324195,"sourceType":"datasetVersion","datasetId":6392219},{"sourceId":10330746,"sourceType":"datasetVersion","datasetId":6396657},{"sourceId":10333654,"sourceType":"datasetVersion","datasetId":6398481},{"sourceId":10333674,"sourceType":"datasetVersion","datasetId":6398497},{"sourceId":10333696,"sourceType":"datasetVersion","datasetId":6398514},{"sourceId":10333791,"sourceType":"datasetVersion","datasetId":6398579},{"sourceId":10334678,"sourceType":"datasetVersion","datasetId":6399195},{"sourceId":10338410,"sourceType":"datasetVersion","datasetId":6401752},{"sourceId":211282696,"sourceType":"kernelVersion"},{"sourceId":211629801,"sourceType":"kernelVersion"},{"sourceId":211653094,"sourceType":"kernelVersion"},{"sourceId":207476,"sourceType":"modelInstanceVersion","modelInstanceId":176874,"modelId":199171},{"sourceId":211175,"sourceType":"modelInstanceVersion","isSourceIdPinned":true,"modelInstanceId":180040,"modelId":202303}],"dockerImageVersionId":30822,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nrid_train_h2o = pd.read_csv('/kaggle/input/rid-train-h2o/submission.csv') # 1.02922\n# p04e12_blended = pd.read_csv('/kaggle/input/p04e12-blended-submission/submission.csv') # 1.02903 - 0.7 Regression ESB - 0.3 H2O\nnew_blended=pd.read_csv('/kaggle/input/final1/submission_blend5.csv') \nregression_ESB = pd.read_csv('/kaggle/input/samplenewtest/submission.csv') \nLGBR_STACK_1 = pd.read_csv('/kaggle/input/insurance-competition-database/LGBR_STACK_1.03088.csv') # 1.03088\naverager_1 = pd.read_csv('/kaggle/input/insurance-competition-database/averager_1.0313127009620042.csv') # 1.03131\ndiff_ev_1 = pd.read_csv('/kaggle/input/insurance-competition-database/diff_ev_1.0313762362011574.csv') # 1.031376","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2024-12-31T03:03:50.634282Z","iopub.execute_input":"2024-12-31T03:03:50.634588Z","iopub.status.idle":"2024-12-31T03:03:53.926154Z","shell.execute_reply.started":"2024-12-31T03:03:50.634556Z","shell.execute_reply":"2024-12-31T03:03:53.925095Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"blended = rid_train_h2o.copy()\n\nblended['Premium Amount'] = (\n    (0.39) * regression_ESB['Premium Amount'] +\n    (0.45) * LGBR_STACK_1['Premium Amount'] +\n    (0.04) * rid_train_h2o['Premium Amount'] +\n    (0.12) * new_blended['Premium Amount'] \n)\n# Save the blended results\nblended.to_csv('submission.csv', index=False)\n\nblended","metadata":{"execution":{"iopub.status.busy":"2024-12-31T03:03:53.927583Z","iopub.execute_input":"2024-12-31T03:03:53.928061Z","iopub.status.idle":"2024-12-31T03:03:55.536395Z","shell.execute_reply.started":"2024-12-31T03:03:53.928029Z","shell.execute_reply":"2024-12-31T03:03:55.535077Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}