{"cells":[{"metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","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 in \n\nprint('hello')\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.","execution_count":2,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"sample = pd.read_csv('../input/train_sample.csv')\nsample.drop(labels=['attributed_time'], inplace=True, axis=1)\n\nX = pd.get_dummies(sample.drop(labels=['is_attributed'], axis=1), sparse=True).values\ny = sample.is_attributed.values\n\nX_train, X_test, y_train, y_test = train_test_split(X, y,  test_size=0.33)\n\n","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"76828528-c1dd-47e4-a0fc-0accf4a8b01c","collapsed":true,"_uuid":"20798f8bdf6668e2f84a0bf3c2051830c8fd76c3","trusted":false},"cell_type":"code","source":"clf = LogisticRegression()\nclf.fit(X_train, y_train)\n","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}