[GitHub] [spark] srowen commented on a change in pull request #26135: [SPARK-29489][ML][PySpark] ml.evaluation support log-loss

[GitBox <gi...@apache.org>]

srowen commented on a change in pull request #26135: [SPARK-29489][ML][PySpark] ml.evaluation support log-loss
URL: https://github.com/apache/spark/pull/26135#discussion_r335586015
 
 

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 File path: mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala
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 @@ -237,4 +239,38 @@ class MulticlassMetrics @Since("1.1.0") (predictionAndLabels: RDD[_ <: Product])
    */
   @Since("1.1.0")
   lazy val labels: Array[Double] = tpByClass.keys.toArray.sorted
+
+  /**
+   * Returns the logLoss, aka logistic loss or cross-entropy loss.
 
 Review comment:
   You could just use a `@return` tag
   Also log-loss rather than logLoss

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