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https://issues.apache.org/jira/browse/FLINK-1966?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14948456#comment-14948456
 ] 

ASF GitHub Bot commented on FLINK-1966:
---------------------------------------

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

    https://github.com/apache/flink/pull/1186#discussion_r41498513
  
    --- Diff: 
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/classification/SVM.scala
 ---
    @@ -228,6 +225,56 @@ class SVM extends Predictor[SVM] {
         parameters.add(OutputDecisionFunction, outputDecisionFunction)
         this
       }
    +
    +  override def toPMML(): PMML = {
    +    weightsOption match {
    +      case None => {
    +        throw new RuntimeException("The SVM model has not been trained. 
Call first fit" +
    +          " before calling the export operation.")
    +      }
    +      case Some(weights) => {
    +        val model = weights.collect().head
    +        val pmml = new PMML()
    +        pmml.setHeader(new Header().setDescription("Support Vector 
Machine"))
    +
    +        // define the fields
    +        val target = FieldName.create("prediction")
    +        val fields = scala.Array.ofDim[FieldName](model.size)
    +        Range(0, model.size).foreach(index =>
    +          fields(index) = FieldName.create("field_" + index)
    +        )
    --- End diff --
    
    Need more scalaesque solution.


> Add support for predictive model markup language (PMML)
> -------------------------------------------------------
>
>                 Key: FLINK-1966
>                 URL: https://issues.apache.org/jira/browse/FLINK-1966
>             Project: Flink
>          Issue Type: Improvement
>          Components: Machine Learning Library
>            Reporter: Till Rohrmann
>            Assignee: Sachin Goel
>            Priority: Minor
>              Labels: ML
>
> The predictive model markup language (PMML) [1] is a widely used language to 
> describe predictive and descriptive models as well as pre- and 
> post-processing steps. That way it allows and easy way to export for and 
> import models from other ML tools.
> Resources:
> [1] 
> http://journal.r-project.org/archive/2009-1/RJournal_2009-1_Guazzelli+et+al.pdf



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