Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/7672#discussion_r35880303
--- 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 --
Yes, posteriorProbabilities is easy to reuse, but it not easy to directly
reuse multinomialCalculation, and bernoulliCalculation because the
mllib.NaiveBayesModel and ml.NaiveBayesModel has different model parameters.
```java
class NaiveBayesModel private[ml] (
override val uid: String,
val pi: Vector,
val theta: Matrix)
```
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