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https://issues.apache.org/jira/browse/FLINK-2297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14608259#comment-14608259
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ASF GitHub Bot commented on FLINK-2297:
---------------------------------------
Github user thvasilo commented on a diff in the pull request:
https://github.com/apache/flink/pull/874#discussion_r33570815
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/classification/SVM.scala
---
@@ -242,8 +275,21 @@ object SVM{
}
}
- override def predict(value: T, model: DenseVector): Double = {
- value.asBreeze dot model.asBreeze
+ override def predict(value: T, model: DenseVector,
predictParameters: ParameterMap):
+ Double = {
+ val thresholdOption = predictParameters.get(Threshold)
+
+ val rawValue = value.asBreeze dot model.asBreeze
+ // If the Threshold option has been reset, we will get back a
Some(None) thresholdOption
+ // causing the exception when we try to get the value. In that
case we just return the
+ // raw value
+ try {
--- End diff --
This part is a bit hacky and will have a performance impact. However it
allows to do what we want without needing to change the way ParameterMap works,
and with the default behaviour being that the thresholdOption is set, the
exception should be triggered most of the time.
> 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
> 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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