[jira] [Issue Comment Deleted] (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:all-tabpanel ]

Kaushik Ranjan updated SPARK-2335:
----------------------------------
    Comment: was deleted

(was: Hi [~bgawalt].

For evaluation of KNN-join, one needs to calculate z-scores of data-points within the dataset.

Yu-ISHIKAWA has implemented the following
https://gist.github.com/yu-iskw/37ae208c530f7018e048

Will it be justified to put up a NewFeature Issue to address z-scores?
)

> 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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