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https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14618323#comment-14618323
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ASF GitHub Bot commented on FLINK-2157:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/871#discussion_r34132488
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/recommendation/ALS.scala
---
@@ -425,6 +434,34 @@ object ALS {
}
}
+ implicit val evaluateRatings = new EvaluateDataSetOperation[ALS, (Int,
Int, Double), Double] {
+ override def evaluateDataSet(
+ instance: ALS,
+ evaluateParameters: ParameterMap,
+ testing: DataSet[(Int, Int, Double)]): DataSet[(Double, Double)] =
{
--- End diff --
return type in next line
> 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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