Grzegorz Chilkiewicz created SPARK-14095:
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Summary: LogisticRegression fails when a DataFrame has only a
one-class label
Key: SPARK-14095
URL: https://issues.apache.org/jira/browse/SPARK-14095
Project: Spark
Issue Type: Bug
Components: ML, MLlib
Affects Versions: 1.6.1
Reporter: Grzegorz Chilkiewicz
Priority: Minor
The problem might look unimportant, but imagine assigning arbitrary weights to
rows or unfortunate splitting on training&test datasets.
Even if the problem is to be ignored, we should return more meaningful error
than "java.lang.ArrayIndexOutOfBoundsException: 1"
I can investigate the problem more deeply and prepare a PR to fix it, or just
intercept the exception and throw a more explanatory one. What should I do?
Code to reproduce the bug:
https://github.com/grzegorz-chilkiewicz/OneNonZeroWeight
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