Marco Gaido commented on SPARK-21340:

[~jake.charland] I submitted a PR but I am not sure it will be merged. If not, 
please use the new ml package.

> Bring PySpark MLLib evaluation metrics to parity with Scala API
> ---------------------------------------------------------------
>                 Key: SPARK-21340
>                 URL: https://issues.apache.org/jira/browse/SPARK-21340
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>    Affects Versions: 2.1.1
>            Reporter: Jake Charland
> This JIRA is a request to bring in PySparks MLLib evaluation metrics to 
> parity with the Scala API. For example in BinaryClassificationMetrics there 
> are only two eval metrics exposed to pyspark, areaUnderROC and areaUnderPR 
> while scala has support for a much wider set of eval metrics including 
> precision recall curves and the ability to set thresholds for recall and 
> precision values. These evaluation metrics are critical for understanding and 
> seeing the performance of trained models and should be available to those 
> using the pyspak api's.

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