Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/7284#discussion_r34639280
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala ---
@@ -0,0 +1,192 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+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.ml.util.Identifiable
+import org.apache.spark.mllib.classification.{NaiveBayes => OldNaiveBayes}
+import org.apache.spark.mllib.classification.{NaiveBayesModel =>
OldNaiveBayesModel}
+import org.apache.spark.mllib.linalg._
+import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.DataFrame
+
+/**
+ * Params for Naive Bayes Classifiers.
+ */
+private[ml] trait NaiveBayesParams extends PredictorParams {
+
+ /**
+ * The smoothing parameter.
+ * (default = 1.0).
+ * @group param
+ */
+ final val lambda: DoubleParam = new DoubleParam(this, "lambda", "The
smoothing parameter.",
+ ParamValidators.gtEq(0))
+
+ /** @group getParam */
+ final def getLambda: Double = $(lambda)
+
+ /**
+ * The model type which is a string (case-sensitive).
+ * Supported options: "multinomial" and "bernoulli".
+ * (default = multinomial)
+ * @group param
+ */
+ final val modelType: Param[String] = new Param[String](this, "modelType",
+ "The model type which is a string (case-sensitive). Supported options:
" +
+ "\"multinomial\" (default) and \"bernoulli\".")
+
+ /** @group getParam */
+ final def getModelType: String = $(modelType)
+}
+
+/**
+ * Naive Bayes Classifiers.
+ * It supports both Multinomial NB
+ *
([[http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html]])
+ * which can handle finitely supported discrete data. For example, by
converting documents into
+ * TF-IDF vectors, it can be used for document classification. By making
every vector a
+ * binary (0/1) data, it can also be used as Bernoulli NB
+ *
([[http://nlp.stanford.edu/IR-book/html/htmledition/the-bernoulli-model-1.html]]).
+ * The input feature values must be nonnegative.
+ */
+class NaiveBayes(override val uid: String)
+ extends Predictor[Vector, NaiveBayes, NaiveBayesModel]
+ with NaiveBayesParams {
+
+ def this() = this(Identifiable.randomUID("nb"))
+
+ /**
+ * Set the smoothing parameter.
+ * Default is 1.0.
+ * @group setParam
+ */
+ def setLambda(value: Double): this.type = set(lambda, value)
+ setDefault(lambda -> 1.0)
+
+ /**
+ * Set the model type using a string (case-sensitive).
+ * Supported options: "multinomial" and "bernoulli".
+ * Default is "multinomial"
+ */
+ def setModelType(value: String): this.type = set(modelType, value)
+ setDefault(modelType -> "multinomial")
+
+ override protected def train(dataset: DataFrame): NaiveBayesModel = {
+ val oldDataset: RDD[LabeledPoint] = extractLabeledPoints(dataset)
+ val oldModel = OldNaiveBayes.train(oldDataset, $(lambda), $(modelType))
+ NaiveBayesModel.fromOld(oldModel, this)
+ }
+
+ override def copy(extra: ParamMap): NaiveBayes = defaultCopy(extra)
+}
+
+/**
+ * Model produced by [[NaiveBayes]]
+ */
+class NaiveBayesModel private[ml] (
+ override val uid: String,
+ val labels: Vector,
--- End diff --
Could you please remove "labels?" I realized this is a major inconsistency
for NaiveBayes. No other model in mllib or ml includes labels. In Pipelines,
this should be handled by StringIndexer beforehand. Sorry I did not think of
this before!
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