From b4574e387d0124667bdbb35f8c7c3e2065b14ba9 Mon Sep 17 00:00:00 2001
From: DB Tsai <dbt@netflix.com>
Date: Thu, 21 Jan 2016 17:24:48 -0800
Subject: [PATCH] [SPARK-12908][ML] Add warning message for LogisticRegression
for potential converge issue
When all labels are the same, it's a dangerous ground for LogisticRegression without intercept to converge. GLMNET doesn't support this case, and will just exit. GLM can train, but will have a warning message saying the algorithm doesn't converge.
Author: DB Tsai <dbt@netflix.com>
Closes #10862 from dbtsai/add-tests.
---
.../spark/ml/classification/LogisticRegression.scala | 8 ++++++++
1 file changed, 8 insertions(+)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index dad8dfc84e..c98a78a515 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -300,6 +300,14 @@ class LogisticRegression @Since("1.2.0") (
s"training is not needed.")
(Vectors.sparse(numFeatures, Seq()), Double.NegativeInfinity, Array.empty[Double])
} else {
+ if (!$(fitIntercept) && numClasses == 2 && histogram(0) == 0.0) {
+ logWarning(s"All labels are one and fitIntercept=false. It's a dangerous ground, " +
+ s"so the algorithm may not converge.")
+ } else if (!$(fitIntercept) && numClasses == 1) {
+ logWarning(s"All labels are zero and fitIntercept=false. It's a dangerous ground, " +
+ s"so the algorithm may not converge.")
+ }
+
val featuresMean = summarizer.mean.toArray
val featuresStd = summarizer.variance.toArray.map(math.sqrt)
--
GitLab