diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala index 97cbaf1fa8761c9d1accd961da3faabd8f1d32b4..69cb88a7e6718df59a63264bc50e520e61c65791 100644 --- a/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala +++ b/mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala @@ -18,11 +18,11 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkException -import org.apache.spark.ml.{PredictorParams, PredictionModel, Predictor} -import org.apache.spark.ml.param.{ParamMap, ParamValidators, Param, DoubleParam} +import org.apache.spark.annotation.Experimental +import org.apache.spark.ml.PredictorParams +import org.apache.spark.ml.param.{DoubleParam, Param, ParamMap, ParamValidators} import org.apache.spark.ml.util.Identifiable -import org.apache.spark.mllib.classification.{NaiveBayes => OldNaiveBayes} -import org.apache.spark.mllib.classification.{NaiveBayesModel => OldNaiveBayesModel} +import org.apache.spark.mllib.classification.{NaiveBayes => OldNaiveBayes, NaiveBayesModel => OldNaiveBayesModel} import org.apache.spark.mllib.linalg._ import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.rdd.RDD @@ -59,6 +59,7 @@ private[ml] trait NaiveBayesParams extends PredictorParams { } /** + * :: Experimental :: * Naive Bayes Classifiers. * It supports both Multinomial NB * ([[http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html]]) @@ -68,6 +69,7 @@ private[ml] trait NaiveBayesParams extends PredictorParams { * ([[http://nlp.stanford.edu/IR-book/html/htmledition/the-bernoulli-model-1.html]]). * The input feature values must be nonnegative. */ +@Experimental class NaiveBayes(override val uid: String) extends ProbabilisticClassifier[Vector, NaiveBayes, NaiveBayesModel] with NaiveBayesParams { @@ -101,11 +103,13 @@ class NaiveBayes(override val uid: String) } /** + * :: Experimental :: * Model produced by [[NaiveBayes]] * @param pi log of class priors, whose dimension is C (number of classes) * @param theta log of class conditional probabilities, whose dimension is C (number of classes) * by D (number of features) */ +@Experimental class NaiveBayesModel private[ml] ( override val uid: String, val pi: Vector,