Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/4140#discussion_r23486231
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/StandardScaler.scala ---
@@ -61,20 +61,30 @@ class StandardScaler(withMean: Boolean, withStd:
Boolean) extends Logging {
* :: Experimental ::
* Represents a StandardScaler model that can transform vectors.
*
- * @param withMean whether to center the data before scaling
- * @param withStd whether to scale the data to have unit standard deviation
* @param mean column mean values
* @param variance column variance values
+ * @param withMean whether to center the data before scaling
+ * @param withStd whether to scale the data to have unit standard deviation
*/
@Experimental
-class StandardScalerModel private[mllib] (
- val withMean: Boolean,
- val withStd: Boolean,
+class StandardScalerModel (
val mean: Vector,
- val variance: Vector) extends VectorTransformer {
+ val variance: Vector,
+ private var withMean: Boolean = false,
+ private var withStd: Boolean = true) extends VectorTransformer {
--- End diff --
Also, users will want to know if `withMean` or `withStd` is used, do we
really need to have them as private variables?
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