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https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14618477#comment-14618477
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ASF GitHub Bot commented on FLINK-2157:
---------------------------------------
Github user thvasilo commented on a diff in the pull request:
https://github.com/apache/flink/pull/871#discussion_r34139345
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/pipeline/Predictor.scala
---
@@ -233,11 +292,10 @@ trait PredictOperation[Instance, Model, Testing,
Prediction] extends Serializabl
* @param model The model representation of the prediciton algorithm
* @return A label for the provided example of type [[Prediction]]
*/
- def predict(value: Testing, model: Model):
- Prediction
+ def predict(value: Testing, model: Model): Prediction
}
-/** Type class for the evaluate operation of [[Predictor]]. This evaluate
operation works on
+/** Trait for the evaluate operation of [[Predictor]]. This evaluate
operation works on
--- End diff --
Will change both back.
> Create evaluation framework for ML library
> ------------------------------------------
>
> Key: FLINK-2157
> URL: https://issues.apache.org/jira/browse/FLINK-2157
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Theodore Vasiloudis
> Labels: ML
> Fix For: 0.10
>
>
> Currently, FlinkML lacks means to evaluate the performance of trained models.
> It would be great to add some {{Evaluators}} which can calculate some score
> based on the information about true and predicted labels. This could also be
> used for the cross validation to choose the right hyper parameters.
> Possible scores could be F score [1], zero-one-loss score, etc.
> Resources
> [1] [http://en.wikipedia.org/wiki/F1_score]
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