_jgrid_r0.py 文件源码

def _cv_LOO_r0( method, xM, yV, alpha, n_jobs = -1, grid_std = None, graph = True):
    """
    method can be 'Ridge', 'Lasso'
    cross validation is performed so as to generate prediction output for all input molecules
    """ 
    n_folds = xM.shape[0]

    print(xM.shape, yV.shape)

    clf = getattr( linear_model, method)( alpha = alpha)
    kf_n = cross_validation.KFold( xM.shape[0], n_folds=n_folds)
    yV_pred = cross_validation.cross_val_predict( clf, xM, yV, cv = kf_n, n_jobs = n_jobs)

    if graph:
        print('The prediction output using cross-validation is given by:')
        jutil.cv_show( yV, yV_pred, grid_std = grid_std)

    return yV_pred