uchiiii commented on code in PR #36920:
URL: https://github.com/apache/spark/pull/36920#discussion_r903171942
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mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala:
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@@ -38,16 +38,14 @@ import org.apache.spark.rdd.RDD
* Since 3.4.0, it supports ndcg evaluation with
relevance value.
*/
@Since("1.2.0")
-class RankingMetrics[T: ClassTag] @Since("3.4.0") (
- predictionAndLabels: RDD[(Array[T], Array[T], Array[Double])])
+class RankingMetrics[T: ClassTag] @Since("1.2.0") (predictionAndLabels: RDD[_
<: Product])
extends Logging
with Serializable {
- @Since("1.2.0")
- def this(predictionAndLabelsWithoutRelevance: => RDD[(Array[T], Array[T])])
= {
- this(predictionAndLabelsWithoutRelevance.map {
- case (pred, lab) => (pred, lab, Array.empty[Double])
- })
+ private val rdd = predictionAndLabels.map {
Review Comment:
We may want not to change the name because
- `MulticlassMetrics` also has the arguments whose name is
`predictionAndLabels`.
https://github.com/apache/spark/blob/b588d070ebc234280af730c8f9915e8859b1886e/mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala#L28-L35
- We change the interface of the constructor to be able to support more
inputs. Specific names like `predictionAndLabelsWithOptionalRelevance` may go
against the goal.
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