srowen commented on a change in pull request #24717: [SPARK-27847][ML] One-Pass
MultilabelMetrics & MulticlassMetrics
URL: https://github.com/apache/spark/pull/24717#discussion_r288139570
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala
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@@ -55,31 +48,59 @@ class MulticlassMetrics @Since("1.1.0")
(predictionAndLabels: RDD[_ <: Product])
throw new IllegalArgumentException(s"Expected Row of tuples, got
$other")
})
- private lazy val labelCountByClass: Map[Double, Double] =
- predLabelsWeight.map {
- case (_: Double, label: Double, weight: Double) =>
- (label, weight)
- }.reduceByKey(_ + _)
+
+ private val confusions = predictionAndLabels.map {
+ case (prediction: Double, label: Double, weight: Double) =>
+ (prediction, label, weight)
+ case (prediction: Double, label: Double) =>
+ (prediction, label, 1.0)
+ case other =>
+ throw new IllegalArgumentException(s"Expected tuples, got $other")
+ }.map { case (prediction: Double, label: Double, weight: Double) =>
+ ((label, prediction), weight)
+ }.reduceByKey(_ + _)
.collectAsMap()
+
+ private lazy val labelCountByClass: Map[Double, Double] = {
Review comment:
OK yeah I was also thinking you could just compute these all non-lazily, and
do so in one pass over confusions, but, maybe not worth it.
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