(self, indices=False, threshold=None)
return mask if not indices else np.where(mask)[0]
Get a mask, or integer index, of the features selected

        Parameters
        ----------
        indices : boolean (default False)
            If True, the return value will be an array of integers,
            rather than a boolean mask.

        threshold: float.
            Threshold defining the minimum cutoff value for the
            stability scores.

        Returns
        -------
        support : array
            An index that selects the retained features from a feature vector.
            If `indices` is False, this is a boolean array of shape
            [# input features], in which an element is True iff its
            corresponding feature is selected for retention. If `indices` is
            True, this is an integer array of shape [# output features] whose
            values are indices into the input feature vector.
Get a mask, or integer index, of the features selected
Get a mask or integer index of the features selected
def get_support(self, indices=False, threshold=None):
        """Get a mask, or integer index, of the features selected

        Parameters
        ----------
        indices : boolean (default False)
            If True, the return value will be an array of integers,
            rather than a boolean mask.

        threshold: float.
            Threshold defining the minimum cutoff value for the
            stability scores.

        Returns
        -------
        support : array
            An index that selects the retained features from a feature vector.
            If `indices` is False, this is a boolean array of shape
            [# input features], in which an element is True iff its
            corresponding feature is selected for retention. If `indices` is
            True, this is an integer array of shape [# output features] whose
            values are indices into the input feature vector.
        """

        if threshold is not None and (not isinstance(threshold, float)
                                      or not (0.0 < threshold <= 1.0)):
            raise ValueError('threshold should be a float in (0, 1], '
                             'got %s' % self.threshold)

        cutoff = self.threshold if threshold is None else threshold
        mask = (self.stability_scores_.max(axis=1) > cutoff)

        return mask if not indices else np.where(mask)[0]
def get_support ( self , indices = False , threshold = None ) : if threshold is not None and ( not isinstance ( threshold , float ) or not ( 0.0 < threshold <= 1.0 ) ) : raise ValueError ( 'threshold should be a float in (0, 1], ' 'got %s' % self . threshold ) cutoff = self . threshold if threshold is None else threshold mask = ( self . stability_scores_ . max ( axis = 1 ) > cutoff ) return mask if not indices else np . where ( mask ) [ 0 ]