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[SPARK-9665] [MLLIB] audit MLlib API annotations

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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.
This commit is contained in:
Xiangrui Meng 2015-08-26 11:47:05 -07:00 committed by Joseph K. Bradley
parent bb16405297
commit 6519fd06cc
1 changed files with 8 additions and 4 deletions
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12
mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
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@ -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,