Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/15435#discussion_r106725381
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -644,21 +644,29 @@ class LogisticRegression @Since("1.2.0") (
val model = copyValues(new LogisticRegressionModel(uid,
coefficientMatrix, interceptVector,
numClasses, isMultinomial))
- // TODO: implement summary model for multinomial case
- val m = if (!isMultinomial) {
- val (summaryModel, probabilityColName) =
model.findSummaryModelAndProbabilityCol()
- val logRegSummary = new BinaryLogisticRegressionTrainingSummary(
+
+ val (summaryModel, probabilityColName, predictionColName)
+ = model.findSummaryModel()
+ val logRegSummary = if (!isMultinomial) {
--- End diff --
We should change this to `if (numClasses <= 2)` since you can train a
multinomial model on 2 classes, and we should still get a binary summary in
that case. And of course, please add tests.
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