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https://issues.apache.org/jira/browse/FLINK-2297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14609807#comment-14609807
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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_r33661424
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/pipeline/Predictor.scala
---
@@ -121,7 +121,7 @@ object Predictor {
input.mapWithBcVariable(model){
(element, model) => {
- (element, predictOperation.predict(element, model))
+ (element, predictOperation.predict(element, model,
resultingParameters))
--- End diff --
Hmm I'm not so sure either what is the best way to go here. My initial idea
was to isolate the predict operation as much as possible from the code
necessary to do the setup. I don't like the `ParameterMap` much, because it
allows you to have access to much more information than necessary. IMO it's
better to extract the information once at one place and then have an explicit
representation of the information.
> 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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