gradient_boosting.py 文件源码

def model_gradient_boosting_tree(Xtrain,Xtest,ytrain):

    X_train = Xtrain
    y_train = ytrain 
    gbr = GradientBoostingRegressor(random_state=0)
    param_grid = {
        'n_estimators': [800,1500],
        'max_features': [20,15],
        'max_depth': [8,10],
        'learning_rate': [0.1],
       'subsample': [1]
    }
    model = GridSearchCV(estimator=gbr, param_grid=param_grid, n_jobs=1, cv=10, scoring=RMSE)
    model.fit(X_train, y_train)
    print('Gradient boosted tree regression...')
    print('Best Params:')
    print(model.best_params_)
    print('Best CV Score:')
    print(-model.best_score_)

    y_pred = model.predict(Xtest)
    return y_pred, -model.best_score_


# read data, build model and do prediction