{"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":"# Ensembling the best public notebooks\n\nCredit for this notebook goes entirely to below public notebooks, kindly appreciate and upvote them\n\n[Indoor GBM+postprocessing XY prediction](https://www.kaggle.com/oxzplvifi/indoor-gbm-postprocessing-xy-prediction)\n\n[wifi features with lightgbm/KFold](https://www.kaggle.com/hiro5299834/wifi-features-with-lightgbm-kfold)\n\n[Simple 👌 99% Accurate Floor Model 💯](https://www.kaggle.com/nigelhenry/simple-99-accurate-floor-model)\n\n[Ensembling for better performance](https://www.kaggle.com/satokiogiso/ensembling-for-better-performance/)\n\n[Indoor navigation snap to grid](https://www.kaggle.com/robikscube/indoor-navigation-snap-to-grid-post-processing)\n\n[Indoor navigation snap to grid Part B](https://www.kaggle.com/mehrankazeminia/part-b-indoor-navigation-snap-to-grid)\n\n[Indoor navigation comparitive method Part A](https://www.kaggle.com/mehrankazeminia/part-a-indoor-navigation-comparative-method)\n\n[Indoor post processing by cost minimization](https://www.kaggle.com/saitodevel01/indoor-post-processing-by-cost-minimization)\n\n[1-3-indoor-navigation-cost-minimization](https://www.kaggle.com/mehrankazeminia/1-3-indoor-navigation-cost-minimization)\n\n[Order to use post processing](https://www.kaggle.com/jerrymark611/order-to-use-post-processing)\n\n[Sequenced Post processing ready prepped for use](https://www.kaggle.com/saurabhbagchi/sequenced-post-processings-ready-prepped-for-use)\n\n[Indoor Navigation Push to hallway post process](https://www.kaggle.com/therocket290/indoor-navigation-push-to-hallway-post-process)\n\n[3-3-g6 Indoor navigation snap to grid](https://www.kaggle.com/mehrankazeminia/3-3-g6-indoor-navigation-snap-to-grid)\n\n[3-3-g6 Indoor navigation snap to grid](https://www.kaggle.com/dragonzhang/3-3-g6-indoor-navigation-snap-to-grid)","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data1 = pd.read_csv(\"../input/indoor-best-submission/submission_6594.csv\")\ndata2 = pd.read_csv(\"../input/indoor-best-submission/submission_6617.csv\")\ndata3 = pd.read_csv(\"../input/indoor-best-submission/submission_6771.csv\")\ndata4 = pd.read_csv(\"../input/indoor-best-submission/submission_7123.csv\")\ndata5 = pd.read_csv(\"../input/indoor-best-submission/submission_6484.csv\")\ndata6 = pd.read_csv(\"../input/indoor-best-submission/submission_6196.csv\")\ndata7 = pd.read_csv(\"../input/indoor-best-submission/i7274cm99.csv\")\ndata8 = pd.read_csv(\"../input/indoor-best-submission/sub_cost_snap.csv\")\ndata9 = pd.read_csv(\"../input/indoor-best-submission/submission_5084.csv\")\ndata10 = pd.read_csv(\"../input/indoor-best-submission/submission_push_to_hallway_ensemble.csv\")\ndata11 = pd.read_csv(\"../input/indoor-best-submission/submission_snap_to_grid_4772.csv\")\ndata12 = pd.read_csv(\"../input/indoor-best-submission/submission (21).csv\")\ndata13 = pd.read_csv(\"../input/indoor-best-submission/submission_snap_to_grid.csv\")\ndata14 = pd.read_csv(\"../input/indoor-best-submission/sub_cost_snap (1).csv\")\ndata15 = pd.read_csv(\"../input/indoor-loc-and-nav-subs/submission_4_483.csv\")\ndata16 = pd.read_csv(\"../input/indoor-loc-and-nav-subs/submission_4_527.csv\")\ndata17 = pd.read_csv(\"../input/indoor-best-submission/submission_4476.csv\")","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data18 = data17\ndata18['x'] = 0.5*data17['x'] + 0.0*data16['x'] + 0.5*data15['x'] + 0.0*data11['x']\ndata18['y'] = 0.5*data17['y'] + 0.0*data16['y'] + 0.5*data15['y'] + 0.0*data11['y']","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data18.head()","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data18.to_csv(\"submission.csv\",index=False)","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\n\n","metadata":{"trusted":true},"execution_count":null,"outputs":[]}]}