Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/11852#discussion_r57121425
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala ---
@@ -326,6 +326,8 @@ class NaiveBayes private (
/** Set the smoothing parameter. Default: 1.0. */
@Since("0.9.0")
def setLambda(lambda: Double): NaiveBayes = {
+ require(lambda > 0,
+ s"Smoothing parameter must be greater than 0 but got ${lambda}")
--- End diff --
Yeah this is looking good, to get all of the same obvious parameter checks
done in one pass. You can say "positive" for "greater than 0" and "nonnegative"
for "greater than or equal to 0" but this is fine.
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