Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/7080#discussion_r33749927
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -98,6 +98,15 @@ class LogisticRegression(override val uid: String)
def setFitIntercept(value: Boolean): this.type = set(fitIntercept, value)
setDefault(fitIntercept -> true)
+ /**
+ * Whether to standardize the training features prior to fitting the
model sequence.
--- End diff --
This is copied from R's description. I think it's about fitting a sequence
of models with different regularization. I will modify it to `to fitting the
model`.
```R
standardize
Logical flag for x variable standardization, prior to fitting the model
sequence.
The coefficients are always returned on the original scale. Default is
standardize=TRUE.
If variables are in the same units already, you might not wish to
standardize.
See details below for y standardization with family="gaussian".
```
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