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Posted to issues@flink.apache.org by "Stavros Kontopoulos (JIRA)" <ji...@apache.org> on 2017/01/17 11:27:26 UTC
[jira] [Commented] (FLINK-1934) Add approximative
k-nearest-neighbours (kNN) algorithm to machine learning library
[ https://issues.apache.org/jira/browse/FLINK-1934?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15825887#comment-15825887 ]
Stavros Kontopoulos commented on FLINK-1934:
--------------------------------------------
Hey guys Is this still active?
> 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: Daniel Blazevski
> 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]. Reference [3] is cited a few times in [1], and gives necessary background on the z-value approach.
> Resources:
> [1] https://www.cs.utah.edu/~lifeifei/papers/mrknnj.pdf
> [2] http://www.computer.org/csdl/proceedings/wacv/2007/2794/00/27940028.pdf
> [3] http://cs.sjtu.edu.cn/~yaobin/papers/icde10_knn.pdf
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