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  1. Spark
  2. SPARK-21340

Bring PySpark MLLib evaluation metrics to parity with Scala API

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Details

    • Improvement
    • Status: Resolved
    • Major
    • Resolution: Incomplete
    • 2.1.1
    • None
    • MLlib

    Description

      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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            Unassigned Unassigned
            jake.charland Jake Charland
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