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https://issues.apache.org/jira/browse/SPARK-2336?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14592815#comment-14592815
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Qiyuan Qiu commented on SPARK-2336:
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Hi [~saurfang] and [~datawlb],
May I ask why both of you based your implementation on the same paper
http://dx.doi.org/10.1109/WACV.2007.18?
It seems to me that the http://ww2.cs.fsu.edu/~czhang/knnjedbt/ mentioned by OP
is reasonably good.
> Approximate k-NN Models for MLLib
> ---------------------------------
>
> Key: SPARK-2336
> URL: https://issues.apache.org/jira/browse/SPARK-2336
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Brian Gawalt
> Priority: Minor
> Labels: clustering, features
>
> After tackling the general k-Nearest Neighbor model as per
> https://issues.apache.org/jira/browse/SPARK-2335 , there's an opportunity to
> also offer approximate k-Nearest Neighbor. A promising approach would involve
> building a kd-tree variant within from each partition, a la
> http://www.autonlab.org/autonweb/14714.html?branch=1&language=2
> This could offer a simple non-linear ML model that can label new data with
> much lower latency than the plain-vanilla kNN versions.
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