This is about the application of One hot encoder. I used label encoder
because it would look like different categorical set of values. (Just to
demonstrate the functionality of One hot encoder)
What I want to know is, what those feature_indices_ and active_features_
indicate. As I've used the same training data (which is the above matrix)
for encoder.fit() and encoder.transform(), all values should be available
in the active_features_ , isn't it?
On Tue, Jul 9, 2013 at 5:15 PM, Lars Buitinck <[email protected]> wrote:
> 2013/7/9 Joel Nothman <[email protected]>:
> > Sorry, I got confused with binarizer somehow. Thanks, Lars.
>
> So did I because LabelBinarizer does not do a one-hot encoding, but
> the general point stands.
>
> --
> Lars Buitinck
> Scientific programmer, ILPS
> University of Amsterdam
>
>
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