[jira] [Commented] (SPARK-2335) k-Nearest Neighbor classification and regression for MLLib

["Kaushik Ranjan (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-2335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14213380#comment-14213380 ] 

Kaushik Ranjan commented on SPARK-2335:
---------------------------------------

Hi [~bgawalt], [~yu_ishikawa]

PFA the code for knnJoin
https://github.com/kaushikranjan/knnJoin

It's in accordance to Algorithm1 from the paper cited below
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5447837&tag=1

Regards,
[~Kaushik619]
[~Rusty]

> k-Nearest Neighbor classification and regression for MLLib
> ----------------------------------------------------------
>
>                 Key: SPARK-2335
>                 URL: https://issues.apache.org/jira/browse/SPARK-2335
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Brian Gawalt
>            Priority: Minor
>              Labels: features
>
> The k-Nearest Neighbor model for classification and regression problems is a simple and intuitive approach, offering a straightforward path to creating non-linear decision/estimation contours. It's downsides -- high variance (sensitivity to the known training data set) and computational intensity for estimating new point labels -- both play to Spark's big data strengths: lots of data mitigates data concerns; lots of workers mitigate computational latency. 
> We should include kNN models as options in MLLib.



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