[SPARK-9665] [MLLIB] audit MLlib API annotations
I only found `ml.NaiveBayes` missing `Experimental` annotation. This PR doesn't cover Python APIs. cc jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #8452 from mengxr/SPARK-9665.
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@ -18,11 +18,11 @@
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package org.apache.spark.ml.classification
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import org.apache.spark.SparkException
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import org.apache.spark.ml.{PredictorParams, PredictionModel, Predictor}
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import org.apache.spark.ml.param.{ParamMap, ParamValidators, Param, DoubleParam}
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import org.apache.spark.annotation.Experimental
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import org.apache.spark.ml.PredictorParams
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import org.apache.spark.ml.param.{DoubleParam, Param, ParamMap, ParamValidators}
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import org.apache.spark.ml.util.Identifiable
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import org.apache.spark.mllib.classification.{NaiveBayes => OldNaiveBayes}
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import org.apache.spark.mllib.classification.{NaiveBayesModel => OldNaiveBayesModel}
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import org.apache.spark.mllib.classification.{NaiveBayes => OldNaiveBayes, NaiveBayesModel => OldNaiveBayesModel}
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import org.apache.spark.mllib.linalg._
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import org.apache.spark.mllib.regression.LabeledPoint
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import org.apache.spark.rdd.RDD
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@ -59,6 +59,7 @@ private[ml] trait NaiveBayesParams extends PredictorParams {
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}
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/**
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* :: Experimental ::
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* Naive Bayes Classifiers.
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* It supports both Multinomial NB
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* ([[http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html]])
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@ -68,6 +69,7 @@ private[ml] trait NaiveBayesParams extends PredictorParams {
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* ([[http://nlp.stanford.edu/IR-book/html/htmledition/the-bernoulli-model-1.html]]).
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* The input feature values must be nonnegative.
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*/
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@Experimental
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class NaiveBayes(override val uid: String)
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extends ProbabilisticClassifier[Vector, NaiveBayes, NaiveBayesModel]
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with NaiveBayesParams {
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@ -101,11 +103,13 @@ class NaiveBayes(override val uid: String)
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}
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/**
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* :: Experimental ::
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* Model produced by [[NaiveBayes]]
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* @param pi log of class priors, whose dimension is C (number of classes)
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* @param theta log of class conditional probabilities, whose dimension is C (number of classes)
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* by D (number of features)
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*/
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@Experimental
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class NaiveBayesModel private[ml] (
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override val uid: String,
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val pi: Vector,
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