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From "Raghav Chalapathy (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1733) Add PCA to machine learning library
Date Wed, 20 May 2015 03:45:00 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1733?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14551753#comment-14551753
] 

Raghav Chalapathy commented on FLINK-1733:
------------------------------------------

Hi Till 
 Let me go through the paper shall present my analysis about the same
with regards
Raghav


> 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: Raghav Chalapathy
>            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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