[
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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
