Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/17086#discussion_r231227854
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala
---
@@ -27,10 +27,17 @@ import org.apache.spark.sql.DataFrame
/**
* Evaluator for multiclass classification.
*
- * @param predictionAndLabels an RDD of (prediction, label) pairs.
+ * @param predAndLabelsWithOptWeight an RDD of (prediction, label, weight)
or
+ * (prediction, label) pairs.
*/
@Since("1.1.0")
-class MulticlassMetrics @Since("1.1.0") (predictionAndLabels: RDD[(Double,
Double)]) {
+class MulticlassMetrics @Since("3.0.0") (predAndLabelsWithOptWeight:
RDD[_]) {
--- End diff --
The python API takes an RDD, creates a DF, and then calls this private
constructor with the DF, but I would think we could just pass the RDD directly
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