Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/10788#discussion_r50041364
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -374,4 +384,85 @@ class LogisticRegressionWithLBFGS
new LogisticRegressionModel(weights, intercept, numFeatures,
numOfLinearPredictor + 1)
}
}
+
+ /**
+ * Run Logistic Regression with the configured parameters on an input RDD
+ * of LabeledPoint entries starting from the initial weights provided.
+ * If a known updater is used calls the ml implementation, to avoid
+ * applying a regularization penalty to the intercept, otherwise
+ * defaults to the mllib implementation. If more than two classes
+ * or feature scaling is disabled, always uses mllib implementation.
+ * If using ml implementation, uses ml code to generate initial weights.
+ */
+ override def run(input: RDD[LabeledPoint]): LogisticRegressionModel = {
+ run(input, generateInitialWeights(input), userSuppliedWeights = false)
+ }
+
+ /**
+ * Run Logistic Regression with the configured parameters on an input RDD
+ * of LabeledPoint entries starting from the initial weights provided.
--- End diff --
Add extra new line before `If a known updater is...`
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