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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