[scikit-learn] Rapid Outlier Detection via Sampling

[Gael Varoquaux]

Dear Orges,

I can see only 33 citations on Google scholar for this paper.

As detailed in the inclusion criteria of scikit-learn:
http://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms
I am afraid that we need many more citations to include this algorithm.

However, you could submit it for inclusion to scikit-learn-contrib:
http://contrib.scikit-learn.org/

Best,

Gaël

On Sat, Nov 25, 2017 at 07:34:42PM +0100, Orges Leka wrote:
> Dear scikit-learn Developers,

> My Name is Orges Leka and I would like to implement 
> "Rapid Outlier Detection via Sampling" [1] in scikit-learn.
> In R this method is already available [2] by the authors of the method.

> In Python I have not seen any implementation yet. The method is very simple yet
> effective as the authors show. First one selects say 20 points. Then computes
> the shortest distance of all other points to these 20 points. This is the
> outlier-score for one specific point. 

> It would be nice to implement this with different metrics / distances (euclid,
> manhattan or other metrics) .

> How would I start the implementation? I have already git-cloned scikit-learn on
> my pc. Do I need to write object oriented or are functions also ok?

> If this succeeds, I would also like to extend the "example-outliers" doc with
> the above method.

> Kind regards
> Dipl. Math. Orges Leka

> [1] https://papers.nips.cc/paper/
> 5127-rapid-distance-based-outlier-detection-via-sampling.pdf
> [2] https://github.com/mahito-sugiyama/sampling-outlier-detection


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-- 
    Gael Varoquaux
    Researcher, INRIA Parietal
    NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France
    Phone:  ++ 33-1-69-08-79-68
    http://gael-varoquaux.info            http://twitter.com/GaelVaroquaux