Feynman Liang created SPARK-12804:
-------------------------------------
Summary: ml.classification.LogisticRegression fails when
FitIntercept with same-label dataset
Key: SPARK-12804
URL: https://issues.apache.org/jira/browse/SPARK-12804
Project: Spark
Issue Type: Bug
Components: ML
Affects Versions: 1.6.0
Reporter: Feynman Liang
When training LogisticRegression on a dataset where the label is all 0 or all
1, an array out of bounds exception is thrown. The problematic code is
{code}
initialCoefficientsWithIntercept.toArray(numFeatures)
= math.log(histogram(1) / histogram(0))
}
{/code}
The correct behaviour is to short-circuit training entirely when only a single
label is present (can be detected from {{labelSummarizer}}) and return a
classifier which assigns all true/false with infinite weights.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
