I thought all the biclustering classes could at least share some scoring functionality. It also might be useful to have properties for converting the bicluster members (`self.rows_` and `self.columns_`) into [other representations](https://github.com/kemaleren/scikit-learn/blob/spectral_biclustering/sklearn/bicluster/util.py#L4).

About the API: I don't know how useful it would be to  simply ignore column clusters. For spectral clustering it might make some sense, but for others it wouldn't. For instance, doing this with Cheng and Church would result in some rows belonging to multiple clusters, and others to none.