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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-2157) Create evaluation framework for ML library
Date Wed, 08 Jul 2015 15:32:06 GMT

    [ https://issues.apache.org/jira/browse/FLINK-2157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14618775#comment-14618775
] 

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_r34161495
  
    --- Diff: flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/pipeline/Predictor.scala
---
    @@ -172,9 +198,42 @@ object Predictor {
           }
         }
       }
    +
    +  /** [[EvaluateDataSetOperation]] which takes a [[PredictOperation]] to calculate a
tuple
    +    * of true label value and predicted label value, when provided with a DataSet of
    +    * [[LabeledVector]].
    +    *
    +    * @param predictOperation An implicit PredictOperation that takes a Flink Vector
and returns
    +    *                         a Double
    +    * @tparam Instance The [[Predictor]] instance that calls the function
    +    * @tparam Model The model that the calling [[Predictor]] uses for predictions
    +    * @return An EvaluateDataSetOperation for LabeledVector
    +    */
    +  implicit def LabeledVectorEvaluateDataSetOperation[
    +  Instance <: Predictor[Instance],
    +  Model](
    +      implicit predictOperation: PredictOperation[Instance, Model, FlinkVector, Double])
    +    : EvaluateDataSetOperation[Instance, LabeledVector, Double] = {
    +    new EvaluateDataSetOperation[Instance, LabeledVector, Double] {
    +      override def evaluateDataSet(
    +          instance: Instance,
    +          evaluateParameters: ParameterMap,
    +          testing: DataSet[LabeledVector])
    +      : DataSet[(Double,  Double)] = {
    --- End diff --
    
    yes :-)


> 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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