Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/12663#discussion_r61312547
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/Classifier.scala ---
@@ -62,6 +65,57 @@ abstract class Classifier[
def setRawPredictionCol(value: String): E = set(rawPredictionCol,
value).asInstanceOf[E]
// TODO: defaultEvaluator (follow-up PR)
+
+ /**
+ * Extract [[labelCol]] and [[featuresCol]] from the given dataset,
+ * and put it in an RDD with strong types.
+ * @throws SparkException if any label is not an integer >= 0
+ */
+ override protected def extractLabeledPoints(dataset: Dataset[_]):
RDD[LabeledPoint] = {
+ dataset.select(col($(labelCol)).cast(DoubleType),
col($(featuresCol))).rdd.map {
+ case Row(label: Double, features: Vector) =>
+ require(label % 1 == 0 && label >= 0, s"Classifier was given
dataset with invalid label" +
--- End diff --
Better yet, I'll just change this to take and check numClasses
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