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https://issues.apache.org/jira/browse/FLINK-1934?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14740627#comment-14740627
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Daniel Blazevski commented on FLINK-1934:
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Hi [~till.rohrmann], Flink seems like a neat project, looking forward to
contributing!
I had indeed looked into H-zkNNJ in Ref [1]. As I had just mentioned in the
exact kNN, I think it will be more wise for me to try an R-tree implementation
of the exact kNN first for my first Flink contribution -- so in the meantime,
how about we don't assign this to me quite yet.
> 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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