def search(X,y):
rmse = make_scorer(RMSE, greater_is_better = False)
param_test1 = {'n_estimators':range(150,401,50)}
gsearch1 = GridSearchCV(estimator = RandomForestRegressor(min_samples_split=30,
min_samples_leaf=20,max_depth=8,max_features='sqrt' ,random_state=10),
param_grid = param_test1, scoring=rmse,cv=5)
gsearch1.fit(X,y)
print gsearch1.grid_scores_, gsearch1.best_params_, gsearch1.best_score_
RandomForest.py 文件源码
python
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