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

["Ashutosh Trivedi (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-2335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14301257#comment-14301257 ] 

Ashutosh Trivedi commented on SPARK-2335:
-----------------------------------------

Hi Brian ,
We extended the implementation to Long with Int,
For doubles there are some approximations, Hopefully we will come-up with double solution, soon.
For latest code please go to this repository
https://github.com/codeAshu/SparkAlgorithms/tree/master/mllib/src/main/scala/org/sparkalgos/mllib/join


_Ashutosh



> 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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