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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2379) Add methods to evaluate field wise statistics over DataSet of vectors.
Date Tue, 18 Aug 2015 13:34:46 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2379?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14701253#comment-14701253
] 

ASF GitHub Bot commented on FLINK-2379:
---------------------------------------

GitHub user sachingoel0101 opened a pull request:

    https://github.com/apache/flink/pull/1032

    [FLINK-2379][ml]Add column wise statistics for vector Data Sets

    This is because of splitting the work in #861 in two parts.

You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/sachingoel0101/flink statistics

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/flink/pull/1032.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #1032
    
----
commit ce433130b909daf3b11c814fa6897af7753404f9
Author: Sachin Goel <sachingoel0101@gmail.com>
Date:   2015-08-18T13:27:53Z

    [FLINK-2379]Adds column statistics for vector Data Sets

----


> Add methods to evaluate field wise statistics over DataSet of vectors.
> ----------------------------------------------------------------------
>
>                 Key: FLINK-2379
>                 URL: https://issues.apache.org/jira/browse/FLINK-2379
>             Project: Flink
>          Issue Type: New Feature
>          Components: Machine Learning Library
>            Reporter: Sachin Goel
>            Assignee: Sachin Goel
>
> Design methods to evaluate statistics over dataset of vectors.
> For continuous fields, Minimum, maximum, mean, variance.
> For discrete fields, Class counts, Entropy, Gini Impurity.
> Further statistical measures can also be supported. For example, correlation between
two series, computing the covariance matrix, etc. 
> [These are currently the things Spark supports.]



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