Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4087#discussion_r26169233
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala ---
@@ -35,26 +39,30 @@ import org.apache.spark.sql.{DataFrame, SQLContext}
* @param pi log of class priors, whose dimension is C, number of labels
* @param theta log of class conditional probabilities, whose dimension is
C-by-D,
* where D is number of features
+ * @param modelType The type of NB model to fit from the enumeration
NaiveBayesModels, can be
+ * Multinomial or Bernoulli
*/
class NaiveBayesModel private[mllib] (
val labels: Array[Double],
val pi: Array[Double],
- val theta: Array[Array[Double]]) extends ClassificationModel with
Serializable with Saveable {
+ val theta: Array[Array[Double]],
+ val modelType: String)
--- End diff --
It might be nice to expose this as the enum-like type instead of a String.
Does that sound reasonable (since users use it when calling NaiveBayes anyways).
It would be good to avoid using "ModelType.fromString" in the predict()
method.
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