Github user leahmcguire commented on a diff in the pull request:
https://github.com/apache/spark/pull/4087#discussion_r26256579
--- 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 --
I had to change this from the enum like type to the string to fix the unit
test failures. An actual enum worked but the substitute that you suggested was
throwing an non-serializable error on all of the NaiveBayes tests.
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