Created
June 5, 2016 13:44
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| from sklearn.tree import DecisionTreeRegressor | |
| import pandas as pd | |
| import numpy as np | |
| train = pd.read_csv('train.csv').set_index('_id') | |
| X = np.array(train.drop(['gain'], 1)) | |
| y = np.array(train['gain']) | |
| model = DecisionTreeRegressor(max_depth=7) | |
| model.fit(X, y) | |
| def get_prediction(row): | |
| x = np.array(row).reshape(1, -1) | |
| prediction = model.predict(x)[0] | |
| return prediction | |
| test = pd.read_csv('test.csv').set_index('_id') | |
| test['prediction'] = test.apply(get_prediction, 1) | |
| test[['prediction']].to_csv('submission.csv') |
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