models.py 文件源码

def scale_features(features, train):
    """Scale features, using test set to learn parameters.

    Returns:
        Scaled copy of features.
    """
    if FLAGS.scaling is None:
        return features
    logging.info('Scaling features with %s', FLAGS.scaling)
    if FLAGS.scaling == 'max_abs':
        scaler = preprocessing.MaxAbsScaler()
    elif FLAGS.scaling == 'standard':
        scaler = preprocessing.StandardScaler()
    else:
        raise ValueError('Unrecognized scaling %s' % FLAGS.scaling)
    scaler.fit(features[train])
    return scaler.transform(features)