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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2297) Add threshold setting for SVM binary predictions
Date Wed, 01 Jul 2015 08:41:04 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14609743#comment-14609743
] 

ASF GitHub Bot commented on FLINK-2297:
---------------------------------------

Github user tillrohrmann commented on a diff in the pull request:

    https://github.com/apache/flink/pull/874#discussion_r33658638
  
    --- Diff: docs/libs/ml/svm.md ---
    @@ -186,5 +199,5 @@ svm.fit(trainingDS)
     val testingDS: DataSet[Vector] = env.readVectorFile(pathToTestingFile)
     
     // Calculate the predictions for the testing data set
    -val predictionDS: DataSet[LabeledVector] = svm.predict(testingDS)
    +val predictionDS: DataSet[(FlinkVector, Double)] = svm.predict(testingDS)
    --- End diff --
    
    Maybe we shouldn't use renaming of imports here. This might be confusing for people not
so familiar with Scala.


> Add threshold setting for SVM binary predictions
> ------------------------------------------------
>
>                 Key: FLINK-2297
>                 URL: https://issues.apache.org/jira/browse/FLINK-2297
>             Project: Flink
>          Issue Type: Improvement
>          Components: Machine Learning Library
>            Reporter: Theodore Vasiloudis
>            Assignee: Theodore Vasiloudis
>            Priority: Minor
>              Labels: ML
>             Fix For: 0.10
>
>
> Currently SVM outputs the raw decision function values when using the predict function.
> We should have instead the ability to set a threshold above which examples are labeled
as positive (1.0) and below negative (-1.0). Then the prediction function can be directly
used for evaluation.



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