[jira] [Commented] (SPARK-14900) spark.ml classification metrics should include accuracy

["Nicholas Chammas (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-14900?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15618637#comment-15618637 ] 

Nicholas Chammas commented on SPARK-14900:
------------------------------------------

I don't know if this belongs in a separate issue, or if it was intended to be addressed as part of this work, but I can't find {{accuracy}} when I look at the methods and attributes available on {{pyspark.ml.classification.BinaryLogisticRegressionTrainingSummary}}.

These are the attributes and methods I see in 2.0.1:

{code}
 'areaUnderROC',
 'fMeasureByThreshold',
 'featuresCol',
 'labelCol',
 'objectiveHistory',
 'pr',
 'precisionByThreshold',
 'predictions',
 'probabilityCol',
 'recallByThreshold',
 'roc',
 'totalIterations'
{code}

Was this an oversight, or am I looking in the wrong place?

> spark.ml classification metrics should include accuracy
> -------------------------------------------------------
>
>                 Key: SPARK-14900
>                 URL: https://issues.apache.org/jira/browse/SPARK-14900
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML
>            Reporter: Joseph K. Bradley
>            Assignee: Miao Wang
>            Priority: Minor
>             Fix For: 2.0.0
>
>
> To compute "accuracy" (0/1 classification accuracy), users can use {{precision}} in MulticlassMetrics and MulticlassClassificationEvaluator.metricName.  We should also support "accuracy" directly as an alias to help users familiar with that name.



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