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From "Timo Walther (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (FLINK-1750) Add canonical correlation analysis (CCA) to machine learning library
Date Tue, 17 Jan 2017 10:08:27 GMT

     [ https://issues.apache.org/jira/browse/FLINK-1750?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Timo Walther updated FLINK-1750:
--------------------------------
    Assignee: Kate Eri  (was: Timo Walther)

> Add canonical correlation analysis (CCA) to machine learning library
> --------------------------------------------------------------------
>
>                 Key: FLINK-1750
>                 URL: https://issues.apache.org/jira/browse/FLINK-1750
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Kate Eri
>              Labels: ML
>
> Canonical correlation analysis (CCA) [1] can be used to find correlated features between
two random variables. Moreover, CCA can be used for dimensionality reduction.
> Maybe the work of Jia Chen and Ioannis D. Schizas [2] can be adapted to realize a distributed
CCA with Flink. 
> Resources:
> [1] [http://en.wikipedia.org/wiki/Canonical_correlation]
> [2] [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6810359]



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