zhengruifeng commented on a change in pull request #25802: [SPARK-29095][ML]
add extractInstances
URL: https://github.com/apache/spark/pull/25802#discussion_r326503592
##########
File path: mllib/src/main/scala/org/apache/spark/ml/Predictor.scala
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@@ -62,6 +62,40 @@ private[ml] trait PredictorParams extends Params
}
SchemaUtils.appendColumn(schema, $(predictionCol), DoubleType)
}
+
+ /**
+ * Extract [[labelCol]], weightCol(if any) and [[featuresCol]] from the
given dataset,
+ * and put it in an RDD with strong types.
+ */
+ protected def extractInstances(dataset: Dataset[_]): RDD[Instance] = {
+ val w = this match {
+ case p: HasWeightCol =>
+ if (isDefined(p.weightCol) && $(p.weightCol).nonEmpty) {
+ col($(p.weightCol)).cast(DoubleType)
+ } else {
+ lit(1.0)
+ }
+ case _ => lit(1.0)
Review comment:
Since this method will only be called internally, so I think it is update to
the developers to decide whether to use it or not. If an algorithm (like GBT)
do not support weighting now, it can use existing `extractLabeledPoints`
instead.
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