RandomForest.py 文件源码

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_