srowen commented on code in PR #36843:
URL: https://github.com/apache/spark/pull/36843#discussion_r896243825
##########
mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala:
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@@ -35,8 +35,16 @@ import org.apache.spark.rdd.RDD
* @param predictionAndLabels an RDD of (predicted ranking, ground truth set)
pairs.
*/
@Since("1.2.0")
-class RankingMetrics[T: ClassTag](predictionAndLabels: RDD[(Array[T],
Array[T])])
- extends Logging with Serializable {
+class RankingMetrics[T: ClassTag](
+ predictionAndLabels: RDD[(Array[T], Array[T], Array[(T, Double)])])
Review Comment:
Hm, why does the last need to be (T, Double) pairs? Wouldn't this be an
attribute of the ground truth? Looking this up via Map seems clunky later. The
problem is not changing the binary signature, but, at least, how about a third
array of Double only, that is parallel to the second array?
##########
mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala:
##########
@@ -58,9 +66,12 @@ class RankingMetrics[T: ClassTag](predictionAndLabels:
RDD[(Array[T], Array[T])]
@Since("1.2.0")
def precisionAt(k: Int): Double = {
Review Comment:
Is there any similar notion of precision@k when the ground truth has a
relevance 'weight'?
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