I mean, say: "If `False`, the `transform` method will return a dense array.
Otherwise, it produces a sparse matrix."


On 27 February 2014 10:46, kaushik94 <notifications@github.com> wrote:

>  In sklearn/preprocessing/data.py:
>
> > @@ -926,6 +926,10 @@ class OneHotEncoder(BaseEstimator, TransformerMixin):
> >
> >      dtype : number type, default=np.float
> >          Desired dtype of output.
> > +
> > +    sparse : boolean
> > +        The function Returns sparse output on setting this to true.
>
> yes i understand this isn't a function but what i meant was that the
> original OneHotEncoder() function will return sparse/dense depending on the
> sparse parameter.
> I dint get what you meant by "make comment in terms of the transform....."
>
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