General question: don't we want to add pipeline modules that convert
between sparse and dense instead of adding the keywords to all estimators?
On May 11, 2014 6:07 PM, "Alexandre Gramfort" <notifications@github.com>
wrote:

> In sklearn/ensemble/forest.py:
>
> > @@ -1270,6 +1270,10 @@ class RandomTreesEmbedding(BaseForest):
> >          If None then unlimited number of leaf nodes.
> >          If not None then ``max_depth`` will be ignored.
> >          Note: this parameter is tree-specific.
> > +
> > +    return_dense : bool, optional (default=False)
> > +        Whether or not to return a sparse CSR matrix, as default behavior,
> > +        or to return a dense matrix compatible with dense pipeline operators.
>
> dense array
>
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>