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https://issues.apache.org/jira/browse/FLINK-1750?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15938392#comment-15938392
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Till Rohrmann commented on FLINK-1750:
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Hi [~kateri],
was there any problem with the implementation of the algorithm or did you
simply not have enough time to work on it?
> 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
> 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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