jgrid.py 文件源码

def cv_LinearRegression_It(xM, yV, n_folds=5, scoring='median_absolute_error', N_it=10, disp=False, ldisp=False):
    """
    N_it times iteration is performed for cross_validation in order to make further average effect. 
    The flag of 'disp' is truned off so each iteration will not shown.  
    """
    cv_score_le = list()
    for ni in range(N_it):
        cv_score_l = cv_LinearRegression(
            xM, yV, n_folds=n_folds, scoring=scoring, disp=disp)
        cv_score_le.extend(cv_score_l)

    o_d = {'mean': np.mean(cv_score_le),
           'std': np.std(cv_score_le),
           'list': cv_score_le}

    if disp or ldisp:
        print('{0}: mean(+/-std) --> {1}(+/-{2})'.format(scoring,
                                                         o_d['mean'], o_d['std']))

    return o_d