[
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:
------------------------------------
Hi [[email protected]],
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
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
