Created
October 26, 2019 02:01
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regr = RandomForestRegressor(random_state = 100,bootstrap = True, max_depth=2,max_features=2,min_samples_leaf=3,min_samples_split=5,n_estimators=3) | |
pipe = Pipeline([ | |
('scaler', StandardScaler()), | |
('reduce_dim', PCA()), | |
('regressor', regr) | |
]) | |
pipe.fit(X_train,y_train) | |
ypipe=pipe.predict(X_test) |
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