(unlabel_x, model)
return pv, spv
Get the probabilistic prediction results of the unlabeled set.

    Parameters
    ----------
    unlabel_x: 2d array
        Feature matrix of the unlabeled set.

    model: object
        Model object which has the method predict_proba.

    Returns
    -------
    pv: np.ndarray
        Probability predictions matrix with shape [n_samples, n_classes].

    spv: tuple
        Shape of pv.
Get the probabilistic prediction results of the unlabeled set.
Get the probabilistic prediction results of the unlabeled set .
def _get_proba_pred(unlabel_x, model):
    """Get the probabilistic prediction results of the unlabeled set.

    Parameters
    ----------
    unlabel_x: 2d array
        Feature matrix of the unlabeled set.

    model: object
        Model object which has the method predict_proba.

    Returns
    -------
    pv: np.ndarray
        Probability predictions matrix with shape [n_samples, n_classes].

    spv: tuple
        Shape of pv.
    """
    if not hasattr(model, 'predict_proba'):
        raise Exception('model object must implement predict_proba methods in current algorithm.')
    pv = model.predict_proba(unlabel_x)
    pv = np.asarray(pv)
    spv = np.shape(pv)
    if len(spv) != 2 or spv[1] == 1:
        raise Exception('2d array with [n_samples, n_class] is expected, but received: \n%s' % str(pv))
    return pv, spv
def _get_proba_pred ( unlabel_x , model ) : if not hasattr ( model , 'predict_proba' ) : raise Exception ( 'model object must implement predict_proba methods in current algorithm.' ) pv = model . predict_proba ( unlabel_x ) pv = np . asarray ( pv ) spv = np . shape ( pv ) if len ( spv ) != 2 or spv [ 1 ] == 1 : raise Exception ( '2d array with [n_samples, n_class] is expected, but received: \n%s' % str ( pv ) ) return pv , spv