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From skavulya <...@git.apache.org>
Subject [GitHub] flink pull request: [FLINK-1979] Add logistic loss, hinge loss and...
Date Thu, 12 May 2016 03:43:14 GMT
GitHub user skavulya opened a pull request:

    https://github.com/apache/flink/pull/1985

    [FLINK-1979] Add logistic loss, hinge loss and regularization penalties 

    Thanks for contributing to Apache Flink. Before you open your pull request, please take
the following check list into consideration.
    If your changes take all of the items into account, feel free to open your pull request.
For more information and/or questions please refer to the [How To Contribute guide](http://flink.apache.org/how-to-contribute.html).
    In addition to going through the list, please provide a meaningful description of your
changes.
    
    - [ ] General
      - The pull request references the related JIRA issue ("[FLINK-XXX] Jira title text")
      - The pull request addresses only one issue
      - Each commit in the PR has a meaningful commit message (including the JIRA id)
    
    - [ ] Documentation
      - Documentation has been added for new functionality
      - Old documentation affected by the pull request has been updated
      - JavaDoc for public methods has been added
    
    - [ ] Tests & Build
      - Functionality added by the pull request is covered by tests
      - `mvn clean verify` has been executed successfully locally or a Travis build has passed
    
    …zation

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

    $ git pull https://github.com/skavulya/flink loss-functions2

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

    https://github.com/apache/flink/pull/1985.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 #1985
    
----
commit 014108ac9ea2e46ac021e9bf3824624d54357f74
Author: spkavuly <soila.p.kavulya@intel.com>
Date:   2016-05-11T22:55:13Z

    Add logistic loss, hinge loss and regularization penalties for optimization

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