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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_r33658953 --- Diff: flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/classification/SVM.scala --- @@ -187,6 +196,26 @@ class SVM extends Predictor[SVM] { parameters.add(Seed, seed) this } + + /** Sets the threshold above which elements are classified as positive + * + * @param threshold + * @return + */ + def setThreshold(threshold: Double): SVM = { + parameters.add(Threshold, threshold) + this + } + + /** Clears the classification threshold, predictions made after calling this function will have + * the raw decision function value. + * + * @return + */ + def clearThreshold(): SVM = { + parameters.add(Threshold, Option.empty[Double]) --- End diff -- It would be better if we have a `parameters.clear(Threshold)` method here. > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)