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From Ashutosh <ashutosh.triv...@iiitb.org>
Subject [MLlib] Contributing Algorithm for Outlier Detection
Date Tue, 21 Oct 2014 09:23:00 GMT
Hi,
I am new to Apache Spark (any open source project). I want to contribute to
it. I found that MLlib has no algorithm for outlier detection yet.  By
literature review I found the algorithm Attribute Value Frequency (AVF) is
promising. Here is the link  DOI: 10.1109/ICTAI.2007.125

By following the process I figured out that, I have to open a new feature
request at JIRA (https://issues.apache.org/jira/browse/SPARK). Also, I have
checked that no other issue is opened on "outlier detection".

I want to know is it the right way to go? What project owners have in mind
about outlier detection? Also is anybody working on parallel K nearest
neighbour?

Apart from opening up the feature request then pull request from git, How to
provide the test cases? 

Suggestions and guidance are welcome.

Thanks,
Ashutosh 



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