jgrid (james-90X3A's conflicted copy 2016-04-21).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