Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/6073#discussion_r30156892
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala ---
@@ -291,6 +294,9 @@ class NaiveBayes private (
if (!values.forall(_ >= 0.0)) {
throw new SparkException(s"Naive Bayes requires nonnegative
feature values but found $v.")
}
+ if (modelType == "Bernoulli" && (!values.forall(v => v == 0.0 || v
== 1.0) )) {
--- End diff --
This should be in a function separate from ```requireNonnegativeValues```
since it should be used in ```createCombiner``` but not ```mergeValue``` in the
aggregation below. I bet the test case with valid input would catch this issue
if it had more rows with non-zeros.
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