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From "Chiwan Park (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (FLINK-1934) Add approximative k-nearest-neighbours (kNN) algorithm to machine learning library
Date Mon, 02 Nov 2015 15:20:27 GMT

     [ https://issues.apache.org/jira/browse/FLINK-1934?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chiwan Park reassigned FLINK-1934:
----------------------------------

    Assignee: Daniel Blazevski  (was: Raghav Chalapathy)

Because [~raghav.chalapathy@gmail.com] is not responded, I assign this issue to [~danielblazevski].

> 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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