Github user dbtsai commented on a diff in the pull request: https://github.com/apache/spark/pull/10788#discussion_r49962408 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala --- @@ -374,4 +383,82 @@ class LogisticRegressionWithLBFGS new LogisticRegressionModel(weights, intercept, numFeatures, numOfLinearPredictor + 1) } } + + /** + * Run the algorithm with the configured parameters on an input RDD + * of LabeledPoint entries starting from the initial weights provided. --- End diff -- Replace `algorithm` by `Logistic Regression`, and remove `starting from the initial weights provided`. Add a new line between `of LabeledPoint entries` and `If a known updater is used`. Actually, in ml version, disabling feature scaling is supported now. So please call ml implementation in this case.
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