From b4574e387d0124667bdbb35f8c7c3e2065b14ba9 Mon Sep 17 00:00:00 2001 From: DB Tsai Date: Thu, 21 Jan 2016 17:24:48 -0800 Subject: [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 Closes #10862 from dbtsai/add-tests. --- .../org/apache/spark/ml/classification/LogisticRegression.scala | 8 ++++++++ 1 file changed, 8 insertions(+) (limited to 'mllib') 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) -- cgit v1.2.3