[jira] [Commented] (FLINK-1934) Add approximative k-nearest-neighbours (kNN) algorithm to machine learning library

["Chiwan Park (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-1934?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14696933#comment-14696933 ] 

Chiwan Park commented on FLINK-1934:
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Hi [~raghav.chalapathy@gmail.com],

Could you tell me about progress of approximate k-NN implementation? Because the costs of an exact k-NN implementation is expensive, I think implementing approximate k-NN should be first.

[~erich.schubert] posted his work about k-NN approximation (http://link.springer.com/chapter/10.1007/978-3-319-18123-3_2). It would help us to discuss and implement this.

> 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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