{"cells":[{"metadata":{"_uuid":"b4b034a256bbf494857127fed186a4f5538415d6"},"cell_type":"markdown","source":"I have used different KFolds techniques with Light GBM Classifier and stacked them together.\n\nThis solution fetched me a Silver medal in the Competition.","execution_count":null},{"metadata":{"trusted":true,"_uuid":"79367977d17b67064ab2b2f5ea3b012657ada3b3"},"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport os\n\nfrom scipy.stats import rankdata\n\nLABELS = [\"HasDetections\"]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"660f76560eb53a35a2471ed3b757b5cb43a2a7f9"},"cell_type":"code","source":"!ls ../input/last-stages","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"7baf1816219bc42c571670616923b54e294a48ad"},"cell_type":"code","source":"!ls ../input/laststages","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"3ed9a7300093e281f26989096abd59682a2afbfb"},"cell_type":"code","source":"!ls ../input/aimalware","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"0a9925c3d96f95fd7598f576038584a66c36bd40"},"cell_type":"code","source":"predict_list = []\npredict_list.append(pd.read_csv(\"../input/aimalware/nffm_submission.csv\")[LABELS].values)\npredict_list.append(pd.read_csv(\"../input/last-stages/submission_ashish_v2.csv\")[LABELS].values)\npredict_list.append(pd.read_csv(\"../input/laststages/submission_ashish_v3.csv\")[LABELS].values)\npredict_list.append(pd.read_csv(\"../input/last-stages/submission_ashish_v4.csv\")[LABELS].values)\npredict_list.append(pd.read_csv(\"../input/last-stages/submission_ashish_vb1.csv\")[LABELS].values)\npredict_list.append(pd.read_csv(\"../input/finalai/blending.csv\")[LABELS].values)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"1b3c1436762f4c9f634745157ec75ca16607b8eb"},"cell_type":"code","source":"print(\"Rank averaging on \", len(predict_list), \" files\")\npredictions = np.zeros_like(predict_list[0])\nfor predict in predict_list:\n    for i in range(1):\n        predictions[:, i] = np.add(predictions[:, i], rankdata(predict[:, i])/predictions.shape[0])  \npredictions /= len(predict_list)\n\nsubmission = pd.read_csv('../input/microsoft-malware-prediction/sample_submission.csv')\nsubmission[LABELS] = predictions\nsubmission.to_csv('super_blend.csv', index=False)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"d09c1af5c618c5d90b8400a3ef66c8e2045929f3"},"cell_type":"code","source":"submission.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"779bf92a803140eeee0e7ff2c6cbc832e087dc22"},"cell_type":"code","source":"#another blend\nsubmission = pd.read_csv('../input/microsoft-malware-prediction/sample_submission.csv')\n\nsample_3 = pd.read_csv(\"../input/last-stages/submission_ashish_v2.csv\")\nsample_4 = pd.read_csv(\"../input/laststages/submission_ashish_v3.csv\")\nsample_5 = pd.read_csv(\"../input/last-stages/submission_ashish_v4.csv\")\nsample_6 = pd.read_csv(\"../input/last-stages/submission_ashish_vb1.csv\")\nsample_7 = pd.read_csv(\"../input/aimalware/nffm_submission.csv\")\nsample_8 = pd.read_csv(\"../input/finalai/blending.csv\")\n\nsubmission['HasDetections'] = sample_6['HasDetections'] * 0.3 + sample_8['HasDetections'] * 0.3 + sample_3['HasDetections'] * 0.2 + sample_7['HasDetections'] * 0.2\nsubmission.to_csv('super_blend_2.csv', index=False)","execution_count":null,"outputs":[]}],"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":4,"nbformat_minor":4}