Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/7080#discussion_r33738207
--- 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 --
"model sequence" may not be understood since we don't provide a sequence
currently; how about just saying "model?"
Also, to make it clear what is meant by standardizing, how about having a
link to StandardScaler.withStd?
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