Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/7672#discussion_r35732493
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala ---
@@ -129,29 +129,49 @@ class NaiveBayesModel private[ml] (
throw new UnknownError(s"Invalid modelType: ${$(modelType)}.")
}
- override protected def predict(features: Vector): Double = {
+ override val numClasses: Int = pi.size
+
+ private def posteriorProbabilities(logProb: DenseVector) = {
--- End diff --
For this, multinomialCalculation, and bernoulliCalculation, can you just
use the versions of the code from spark.mllib? It looks like they can be made
static easily by passing model parameters as needed. That will reduce code
duplication.
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