Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/12663#discussion_r60959821
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala ---
@@ -126,16 +126,8 @@ final class GBTClassifier @Since("1.4.0") (
override protected def train(dataset: Dataset[_]):
GBTClassificationModel = {
val categoricalFeatures: Map[Int, Int] =
MetadataUtils.getCategoricalFeatures(dataset.schema($(featuresCol)))
- val numClasses: Int =
MetadataUtils.getNumClasses(dataset.schema($(labelCol))) match {
- case Some(n: Int) => n
- case None => throw new IllegalArgumentException("GBTClassifier was
given input" +
- s" with invalid label column ${$(labelCol)}, without the number of
classes" +
- " specified. See StringIndexer.")
- // TODO: Automatically index labels: SPARK-7126
- }
- require(numClasses == 2,
- s"GBTClassifier only supports binary classification but was given
numClasses = $numClasses")
--- End diff --
This error message is somewhat more informative to users than
https://github.com/apache/spark/pull/12663/files#diff-dfca98acb06778e7a51eb858829bd2a1R134,
i.e. indicating that GBT only supports binary classification as of now.
Perhaps we should preserve this somehow?
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