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https://issues.apache.org/jira/browse/FLINK-1733?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15159603#comment-15159603
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Thang Nguyen edited comment on FLINK-1733 at 2/23/16 8:40 PM:
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Hey folks, just wanted to update you on my progress:
I'm still trying to work through an SPCA implementation, but I was hoping to
get some preliminary feedback. Instead of showing something half implemented, I
decided to clean up the naive PCA implementation.
You can see the code
[here|https://github.com/nguyent/flink/commit/8f198edcf26c6a98f8c7cdb7c30ef96632ec6f8c].
Any and all feedback is welcome, especially around code organization and
general style.
was (Author: thang):
Hey folks, just wanted to update you on my progress:
I'm still trying to work through an SPCA implementation, but I was hoping to
get some preliminary feedback.
Instead of showing something half implemented, I decided to clean up the naive
PCA implementation. You can see the code
[here|https://github.com/nguyent/flink/commit/8f198edcf26c6a98f8c7cdb7c30ef96632ec6f8c]
Any and all feedback is welcome, especially around code organization and
general style.
> Add PCA to machine learning library
> -----------------------------------
>
> Key: FLINK-1733
> URL: https://issues.apache.org/jira/browse/FLINK-1733
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Thang Nguyen
> Priority: Minor
> Labels: ML
>
> Dimension reduction is a crucial prerequisite for many data analysis tasks.
> Therefore, Flink's machine learning library should contain a principal
> components analysis (PCA) implementation. Maria-Florina Balcan et al. [1]
> proposes a distributed PCA. A more recent publication [2] describes another
> scalable PCA implementation.
> Resources:
> [1] [http://arxiv.org/pdf/1408.5823v5.pdf]
> [2] [http://ds.qcri.org/images/profile/tarek_elgamal/sigmod2015.pdf]
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