Hi Raghav,
Thanks a lot for the idea. I would be glad to work on it and along with the
"output dummy one-hot encoder features for imputer to specify if the feature
value is imputed or not", would the the idea to add " binary indicator
feature (for each possibly missing feature) that indicate feature
was imputed" as suggested here
<https://github.com/scikit-learn/scikit-learn/issues/6556> probably be a
nice and easy addition ?
Thanks,
Maniteja.
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On Fri, Mar 25, 2016 at 9:25 PM, Andreas Mueller <t3k...@gmail.com> wrote:
>
>
> On 03/25/2016 11:11 AM, Raghav R V wrote:
> > Hey Maniteja,
> >
> > I took a look at your proposal. As I said before I feel it is a bit
> > broad and you should try to narrow it down to a good theme.
> >
> > Since you have chosen more than one PRs which are missing value
> > related, I have a suggestion for a theme -
> >
> > "Better Missing Value Handling"
> >
> > You could group the knn imputation, matrix factorization with missing
> > values and *outputting dummy one-hot encoded features for imputer to
> > specify if the feature value is imputed or not. Implementing these
> > properly and merging should be sufficient for a GSoC I feel. As an
> > optional thing, you could add another imputation strategy.
> >
> > *I'll raise an issue so you understand that better.
> +1
>
>
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