Yes! Exactly the same!
On Fri, Mar 25, 2016 at 6:21 PM, Maniteja Nandana <
maniteja.modesty...@gmail.com> wrote:
> 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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>
>
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