[scikit-learn] Machine learning for PU data

[Nicolas Goix]

Hello,

As mentioned by Roman, you can try the one-class scikit-learn algorithms
such as OneClassSVM, IsolationForest, LocalOutlierFactor (with the private
predict method) or EllipticEnvelope.

Hope this helps
Nicolas

On Fri, Jun 30, 2017 at 3:39 PM, Roman Yurchak <rth.yurchak at gmail.com>
wrote:

> Hello Ruchika,
>
> I don't think that scikit-learn currently has algorithms that can train
> with positive and unlabeled class labels only. However, you could try one
> of the following compatible wrappers,
>   - http://nktmemo.github.io/jekyll/update/2015/11/07/pu_classif
> ication.html
>   - https://github.com/scikit-learn/scikit-learn/pull/371
>
> (haven't tried them myself).
>
> Also, you could try one class SVM as suggested here
> https://stackoverflow.com/questions/25700724/binary-semi-
> supervised-classification-with-positive-only-and-unlabeled-data-set
>
> --
> Roman
>
>
>
>
> On 30/06/17 16:06, Ruchika Nayyar wrote:
>
>> Hi All,
>>
>> I am a scikit-learn user and have a question for the community, if
>> anyone has applied any available machine learning algorithms in the
>> scikit-learn package for data with positive and unlabeled class only? If
>> so would you share some insight with me. I understand this could be a
>> broader topic but I am new to analyzing PU data and hence can use some
>> help.
>>
>> Thanks,
>> Ruchika
>>
>>
>>
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