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Posted to reviews@spark.apache.org by yanboliang <gi...@git.apache.org> on 2016/05/05 10:57:18 UTC

[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

GitHub user yanboliang opened a pull request:

    https://github.com/apache/spark/pull/12930

    [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiveBayes error when label is numeric type

    ## What changes were proposed in this pull request?
    Fix SparkR ```spark.naiveBayes``` error when label is numeric type.
    See details about how to reproduce this bug at [SPARK-15153](https://issues.apache.org/jira/browse/SPARK-15153).
    
    ## How was this patch tested?
    Add unit test.


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

    $ git pull https://github.com/yanboliang/spark spark-15153

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

    https://github.com/apache/spark/pull/12930.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 #12930
    
----
commit bc2c0a372930392285abd27d11926e131e617822
Author: Yanbo Liang <yb...@gmail.com>
Date:   2016-05-05T10:50:54Z

    Fix SparkR spark.naiveBayes error when label is numeric type

----


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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-217133042
  
    Test PASSed.
    Refer to this link for build results (access rights to CI server needed): 
    https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/57877/
    Test PASSed.


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[GitHub] spark issue #12930: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiveBayes ...

Posted by jkbradley <gi...@git.apache.org>.
Github user jkbradley commented on the issue:

    https://github.com/apache/spark/pull/12930
  
    It's still a problem.  (I just tried the unit test on master.)  Sorry for the delay @yanboliang !


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[GitHub] spark issue #12930: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiveBayes ...

Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on the issue:

    https://github.com/apache/spark/pull/12930
  
    Should/Would this be better if this is handled in the RFormula level? I could see other models could benefit from this too, in addition to just R.


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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by mengxr <gi...@git.apache.org>.
Github user mengxr commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-220529140
  
    Is it okay to always cast the target label column to string?


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[GitHub] spark issue #12930: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiveBayes ...

Posted by felixcheung <gi...@git.apache.org>.
Github user felixcheung commented on the issue:

    https://github.com/apache/spark/pull/12930
  
    Do we still need this?



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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-217132865
  
    **[Test build #57877 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57877/consoleFull)** for PR 12930 at commit [`bc2c0a3`](https://github.com/apache/spark/commit/bc2c0a372930392285abd27d11926e131e617822).
     * This patch passes all tests.
     * This patch merges cleanly.
     * This patch adds no public classes.


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[GitHub] spark issue #12930: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiveBayes ...

Posted by jkbradley <gi...@git.apache.org>.
Github user jkbradley commented on the issue:

    https://github.com/apache/spark/pull/12930
  
    Oh!  Now I see the JIRA's linked JIRA.  I agree that updating RFormula is a better solution and that we can close this PR.  I'll check out the other PR.


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[GitHub] spark pull request #12930: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiv...

Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang closed the pull request at:

    https://github.com/apache/spark/pull/12930


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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by SparkQA <gi...@git.apache.org>.
Github user SparkQA commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-217125567
  
    **[Test build #57877 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/57877/consoleFull)** for PR 12930 at commit [`bc2c0a3`](https://github.com/apache/spark/commit/bc2c0a372930392285abd27d11926e131e617822).


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[GitHub] spark issue #12930: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.naiveBayes ...

Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on the issue:

    https://github.com/apache/spark/pull/12930
  
    Move the new fix to #15431 which leverages ```RFormula forceIndexLabel```, more succinct.


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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-217146980
  
    cc @mengxr @jkbradley 


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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-217133039
  
    Merged build finished. Test PASSed.


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[GitHub] spark pull request: [SPARK-15153] [ML] [SparkR] Fix SparkR spark.n...

Posted by yanboliang <gi...@git.apache.org>.
Github user yanboliang commented on the pull request:

    https://github.com/apache/spark/pull/12930#issuecomment-220610054
  
    It's feasible to always cast the target label column to string, but we should refactor ```RFormula```. ```RFormula``` handles label of numeric type and string type differently, we should unified them. But I'm not sure whether we can finish that before 2.0.


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