jgrid.py 文件源码

def gs_Ridge(xM, yV, alphas_log=(1, -1, 9), n_folds=5, n_jobs=-1, scoring='r2'):
    """
    Parameters
    -------------
    scoring: mean_absolute_error, mean_squared_error, median_absolute_error, r2
    """
    print('If scoring is not r2 but error metric, output score is revered for scoring!')
    print(xM.shape, yV.shape)

    clf = linear_model.Ridge()
    #parmas = {'alpha': np.logspace(1, -1, 9)}
    parmas = {'alpha': np.logspace(*alphas_log)}
    kf_n_c = model_selection.KFold(n_splits=n_folds, shuffle=True)
    kf_n = kf_n_c.split(xM)
    gs = model_selection.GridSearchCV(
        clf, parmas, scoring=scoring, cv=kf_n, n_jobs=n_jobs)

    gs.fit(xM, yV)

    return gs