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From "Daniel Blazevski (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1934) Add approximative k-nearest-neighbours (kNN) algorithm to machine learning library
Date Thu, 10 Sep 2015 19:37:45 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1934?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14739437#comment-14739437

Daniel Blazevski commented on FLINK-1934:


I have been thinking about implementing a distributed, scalable implementation of kNN and
would like to know the current progress of anyone working on it before diving into the project.

> Add approximative k-nearest-neighbours (kNN) algorithm to machine learning library
> ----------------------------------------------------------------------------------
>                 Key: FLINK-1934
>                 URL: https://issues.apache.org/jira/browse/FLINK-1934
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Raghav Chalapathy
>              Labels: ML
> kNN is still a widely used algorithm for classification and regression. However, due
to the computational costs of an exact implementation, it does not scale well to large amounts
of data. Therefore, it is worthwhile to also add an approximative kNN implementation as proposed
in [1,2].
> Resources:
> [1] https://www.cs.utah.edu/~lifeifei/papers/mrknnj.pdf
> [2] http://www.computer.org/csdl/proceedings/wacv/2007/2794/00/27940028.pdf

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