Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4087#discussion_r25727335
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala ---
@@ -66,11 +84,18 @@ class NaiveBayesModel private[mllib] (
}
override def predict(testData: Vector): Double = {
- labels(brzArgmax(brzPi + brzTheta * testData.toBreeze))
+ modelType match {
+ case NaiveBayesModels.Multinomial =>
+ labels (brzArgmax (brzPi + brzTheta * testData.toBreeze) )
+ case NaiveBayesModels.Bernoulli =>
+ labels (brzArgmax (brzPi +
+ (brzTheta - brzNegTheta.get) * testData.toBreeze +
+ brzSum(brzNegTheta.get, Axis._1)))
--- End diff --
This sum could be precomputed. I'm also wondering: Is there some
normalization going on here which isn't needed to get the argmax?
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