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Last active October 3, 2019 12:55
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gistfile1.txt
comp = pd.read_csv('top 1 sample.csv')
weights = pd.Series({'ridge':0.25, 'lasso':0.25, 'ElasticNet':0.25, 'svm':0.01,'forest':0.01, 'gradient boost':0.1, 'xgboost':0.13})
# adjusting weights to minimize mean square error root with top 1 submission
np.sqrt((((submissions.drop('Id', 1)*weights).sum(axis=1)-comp['SalePrice'])**2).mean())
submissions['blend']=np.round((submissions*weights).sum(axis=1), 1)
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