kgrid_r0.py 文件源码

def cv_Ridge_BIKE( A_list, yV, XX = None, alpha = 0.5, n_splits = 5, n_jobs = -1, grid_std = None):

    clf = binary_model.BIKE_Ridge( A_list, XX, alpha = alpha)
    ln = A_list[0].shape[0] # ls is the number of molecules.
    kf_n_c = model_selection.KFold( n_splits = n_splits, shuffle=True)
    kf_n = kf5_ext_c.split( A_list[0])

    AX_idx = np.array([list(range( ln))]).T
    yV_pred = model_selection.cross_val_predict( clf, AX_idx, yV, cv = kf_n, n_jobs = n_jobs)

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

    return yV_pred