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-rw-r--r--mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala4
1 files changed, 4 insertions, 0 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
index c3882606d7..f807b5683c 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
@@ -408,6 +408,10 @@ class LogisticRegressionWithLBFGS
* defaults to the mllib implementation. If more than two classes
* or feature scaling is disabled, always uses mllib implementation.
* Uses user provided weights.
+ *
+ * In the ml LogisticRegression implementation, the number of corrections
+ * used in the LBFGS update can not be configured. So `optimizer.setNumCorrections()`
+ * will have no effect if we fall into that route.
*/
override def run(input: RDD[LabeledPoint], initialWeights: Vector): LogisticRegressionModel = {
run(input, initialWeights, userSuppliedWeights = true)