Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/7875#discussion_r36049752
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
@@ -85,6 +85,18 @@ class LinearRegression(override val uid: String)
setDefault(fitIntercept -> true)
/**
+ * Whether to standardize the training features before fitting the model.
+ * The coefficients of models will be always returned on the original
scale,
+ * so it will be transparent for users. Note that when no regularization,
+ * with or without standardization, the models should be always
converged to
+ * the same solution.
+ * Default is true.
+ * @group setParam
+ */
+ def setStandardization(value: Boolean): this.type = set(standardization,
value)
+ setDefault(standardization -> true)
--- End diff --
The old behavior is true. Should we mention it since it's just a new
feature?
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