{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Building ensemble, let's go!\n\nI used these notebooks:\n* https://www.kaggle.com/code/thedevastator/the-fine-art-of-hyperparameter-tuning\n* https://www.kaggle.com/code/ragnar123/amex-lgbm-dart-cv-0-7977\n\nI trained 4 boostings using ragnar notebook and just used prediction from the thedevastator one, then used 0.8*(average of \"ragnars\" boostings) + 0.2*(\"thedevastator\" boosting). I'm still not sure about submission robustness, sometimes it looks like just overfitting the public lb. I want to train more boostings on different hyperparams in future to get more robustness.","metadata":{}},{"cell_type":"code","source":"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-07-18T23:36:42.264739Z","iopub.execute_input":"2022-07-18T23:36:42.265944Z","iopub.status.idle":"2022-07-18T23:36:42.271833Z","shell.execute_reply.started":"2022-07-18T23:36:42.265886Z","shell.execute_reply":"2022-07-18T23:36:42.270174Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Let's hope it is (but nobody knows)\nsub = pd.read_csv('../input/amex-subs/gold_medal_score_secret.csv')\nsub.to_csv('submission.csv', index = False)","metadata":{"execution":{"iopub.status.busy":"2022-07-18T23:36:42.407296Z","iopub.execute_input":"2022-07-18T23:36:42.407958Z","iopub.status.idle":"2022-07-18T23:36:49.922687Z","shell.execute_reply.started":"2022-07-18T23:36:42.407885Z","shell.execute_reply":"2022-07-18T23:36:49.921296Z"},"trusted":true},"execution_count":null,"outputs":[]}]}