{"cells":[{"metadata":{},"cell_type":"markdown","source":"## In this notebook, we make an attempt to improve our blending(Or ensembling) by using ranks instead of absolute numbers.\n![image.png](attachment:image.png)\n#### Reasoning behind this logic is that the ROC-AUC metric used here only cares about the rank of the prediction(Explained Below)","attachments":{"image.png":{"image/png":"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"}},"execution_count":null},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\n# for dirname, _, filenames in os.walk('/kaggle/input'):\n#     for filename in filenames:\n#         print(os.path.join(dirname, filename))\n\n# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"os.listdir('../input/efficientnets/')\nPATH = 'input/efficientnets'","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dfs = []\ni = 0\nfor df_loc in os.listdir('../input/efficientnets/'):\n    print('../input/efficientnets/{}'.format(df_loc))\n    df = pd.read_csv('../input/efficientnets/{}'.format(df_loc))\n#     df.head()\n    dfs.append(df)\n# dfs    ","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"> **Dmytro Danevskyi wrote:**\n> \n> The target metric in this competition is based on ranks rather than on actual values. That means that as long as the order of your values is fixed, the metric will stay the same.\n> \n> To illustrate:\n> \n> ```\n> target = [1, 0, 1, 1, 0]\n> preds = [0.5, 0.25, 0.2, 0.3, 0.1]\n> \n> metric = roc_auc_score(target, preds)  # 0.833\n> \n> target = [1, 0, 1, 1, 0]\n> preds = [0.7, 0.15, 0.1, 0.2, 0.05]\n> \n> metric = roc_auc_score(target, preds)  # 0.833\n> ```\n> \n> As you can see, only the rank of the predictions matters. Not the actual value.\n\n> That means that two different models that give the **same** score could actually output completely **different** values. They are not even required to be in (0, 1) range!\n> \n> ```\n> target = [1, 0, 1, 1, 0]\n> preds = [100, 25, 20, 30, 10]\n> \n> metric = roc_auc_score(target, preds)  # 0.833\n> ```\n> \n> Then, if you will try to average the predictions of two non-calibrated models, you might observe that the score is not necessarily getting better and in some cases, it could become even worse! This happens because the prediction scales of these two models are not directly comparable because of the aforementioned issue.\n> \n> How this can be fixed?\n> \n> One simple solution is to bring the predictions to the same scale, e.g. with `scipy.stats.rankdata` function. This will turn scores into ranks, i.e. `[0.7, 0.15, 0.1, 0.2, 0.05]` will be turned into `[5, 3, 2, 4, 1]`. After this, the predictions could be blended.\n> \n> Note that this not always lead to better results and is highly dependent on which exactly models are blended, how strong is the bias, and so on.\n> \n> To illustrate, I decided to naively blend my best scoring model (ResNet18) that gives 0.914 on the public leaderboard with the best-scoring public kernel available (0.927) and I got 0.925. After I preprocessed both predictions with `rankdata`, my score improved to 0.933.\n\n","execution_count":null},{"metadata":{},"cell_type":"markdown","source":"## Taking advantage of this information, let's try blending using rank\n* (Not absolute values)\n* Previous score was 0.888","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"from scipy.stats import rankdata","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for i in range(4) :\n    dfs[i]['target'] = rankdata(dfs[i]['target'], method='min')\n# dfs[0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dfs[0]['target'] = (dfs[0]['target'] + dfs[1]['target'] + dfs[2]['target'] + dfs[3]['target'])/4","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dfs[0]","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"* Ranking again","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"\ndfs[0]['target'] = rankdata(dfs[0]['target'], method='min')\ndfs[0].to_csv('sol.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}