zhengruifeng 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_r335326955
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/MulticlassMetrics.scala
##########
@@ -28,28 +28,30 @@ import org.apache.spark.sql.{DataFrame, Row}
/**
* Evaluator for multiclass classification.
*
- * @param predictionAndLabels an RDD of (prediction, label, weight) or
- * (prediction, label) tuples.
+ * @param predictionAndLabels an RDD of (prediction, label, weight,
probability) or
+ * (prediction, label, weight) or (prediction,
label) tuples.
*/
@Since("1.1.0")
class MulticlassMetrics @Since("1.1.0") (predictionAndLabels: RDD[_ <:
Product]) {
/**
* An auxiliary constructor taking a DataFrame.
- * @param predictionAndLabels a DataFrame with two double columns:
prediction and label
+ * @param predictionAndLabels a DataFrame with columns: prediction, label,
weight(optional)
+ * and probability(only for logloss)
*/
private[mllib] def this(predictionAndLabels: DataFrame) =
- this(predictionAndLabels.rdd.map {
- case Row(prediction: Double, label: Double, weight: Double) =>
- (prediction, label, weight)
- case Row(prediction: Double, label: Double) =>
- (prediction, label, 1.0)
- case other =>
- throw new IllegalArgumentException(s"Expected Row of tuples, got
$other")
+ this(predictionAndLabels.rdd.map { r =>
+ r.size match {
+ case 2 => (r.getDouble(0), r.getDouble(1), 1.0, null)
+ case 3 => (r.getDouble(0), r.getDouble(1), r.getDouble(2), null)
+ case 4 => (r.getDouble(0), r.getDouble(1), r.getDouble(2),
r.getSeq[Double](3).toArray)
+ case _ => throw new IllegalArgumentException(s"Expected Row of tuples,
got $r")
+ }
})
-
- private val confusions = predictionAndLabels.map {
+ private lazy val confusions = predictionAndLabels.map {
Review comment:
If the metricName==logloss, then the confusion matrix is not needed, so I
make this computation lazy.
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