model.py 文件源码

def fit_boosting(X, y, window=100000, estimators=250, learning=.01,
                 samples_leaf=500, depth=20, validate=False):
    '''
    Fits Gradient Boosting
    '''
    model = GradientBoostingRegressor(n_estimators=estimators,
                                      learning_rate=learning,
                                      min_samples_leaf=samples_leaf,
                                      max_depth=depth,
                                      random_state=42)
    if validate:
        return cross_validate(X, y, model, window)
    return model.fit(X, y)