zhengruifeng commented on a change in pull request #25983:
[SPARK-29327][MLLIB]Support specifying features via multiple columns
URL: https://github.com/apache/spark/pull/25983#discussion_r337431082
##########
File path: mllib/src/main/scala/org/apache/spark/ml/Predictor.scala
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@@ -127,6 +136,27 @@ abstract class Predictor[
/** @group setParam */
def setPredictionCol(value: String): Learner = set(predictionCol,
value).asInstanceOf[Learner]
+ /**
+ * @group setParam
+ * An overloaded version to support multiple columns for features.
+ *
+ * Please note it will save the features columns names to a new parameter
"featuresCols" as
+ * an Array[String].
+ */
+ def setFeaturesCol(value: Array[String]): Learner = {
+ require(isSupportMultiColumnsForFeatures,
+ s"Multiple columns for features is not supported by
${getClass.getSimpleName}")
+ set(featuresCols, value).asInstanceOf[Learner]
+ }
+
+ /**
+ * Children classes should override this to tell whether supporting multiple
columns
+ * for features, meaning to fetch features columns names from parameter
'featuresCols'.
+ *
+ * @return Whether this predictor support multiple columns for features
+ */
+ protected def isSupportMultiColumnsForFeatures: Boolean = false
Review comment:
I do not see the impl that support fit/transform in
Predictor/PredictionModel, it seems that in this PR all algs in ML do not impl
this new fit/transform with more features cols?
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