def _transform_scaling(est, in_names=None):
if in_names is None:
in_names = _get_feature_names(est,
feature_names=in_names,
num_features=est.scale_.shape[0])
return [name for name in in_names]
def _select_names(est, in_names=None):
mask = est.get_support(indices=False)
in_names = _get_feature_names(est,
feature_names=in_names,
num_features=len(mask))
return [in_names[i] for i in np.flatnonzero(mask)]