org.apache.spark.ml.classification

Class NaiveBayes

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<M>

org.apache.spark.ml.Predictor<FeaturesType,E,M>

org.apache.spark.ml.classification.Classifier<FeaturesType,E,M>

org.apache.spark.ml.classification.ProbabilisticClassifier<Vector,NaiveBayes,NaiveBayesModel>

org.apache.spark.ml.classification.NaiveBayes

All Implemented Interfaces:

java.io.Serializable, Logging, ClassifierParams, NaiveBayesParams, ProbabilisticClassifierParams, Params, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasProbabilityCol, HasRawPredictionCol, HasThresholds, HasWeightCol, PredictorParams, DefaultParamsWritable, Identifiable, MLWritable

public class NaiveBayes
extends ProbabilisticClassifier<Vector,NaiveBayes,NaiveBayesModel>
implements NaiveBayesParams, DefaultParamsWritable

Naive Bayes Classifiers. It supports Multinomial NB (see here) 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 (see here). The input feature values must be nonnegative.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
NaiveBayes()
NaiveBayes(String uid)

Method Summary

Modifier and Type	Method and Description
NaiveBayes	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static NaiveBayes	load(String path)
static MLReader<T>	read()
NaiveBayes	setModelType(String value) Set the model type using a string (case-sensitive).
NaiveBayes	setSmoothing(double value) Set the smoothing parameter.
NaiveBayes	setWeightCol(String value) Sets the value of param weightCol.
String	uid() An immutable unique ID for the object and its derivatives.

Methods inherited from class org.apache.spark.ml.classification.ProbabilisticClassifier

setProbabilityCol, setThresholds

Methods inherited from class org.apache.spark.ml.classification.Classifier

setRawPredictionCol

Methods inherited from class org.apache.spark.ml.Predictor

fit, setFeaturesCol, setLabelCol, setPredictionCol, transformSchema

Methods inherited from class org.apache.spark.ml.Estimator

fit, fit, fit, fit

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.classification.NaiveBayesParams

getModelType, getSmoothing, modelType, smoothing

Methods inherited from interface org.apache.spark.ml.PredictorParams

validateAndTransformSchema

Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

getLabelCol, labelCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

featuresCol, getFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString

Methods inherited from interface org.apache.spark.ml.param.shared.HasWeightCol

getWeightCol, weightCol

Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable

write

Methods inherited from interface org.apache.spark.ml.util.MLWritable

save

Methods inherited from interface org.apache.spark.ml.classification.ProbabilisticClassifierParams

validateAndTransformSchema

Methods inherited from interface org.apache.spark.ml.param.shared.HasRawPredictionCol

getRawPredictionCol, rawPredictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasProbabilityCol

getProbabilityCol, probabilityCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasThresholds

getThresholds, thresholds

Methods inherited from interface org.apache.spark.internal.Logging

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

NaiveBayes

public NaiveBayes(String uid)

NaiveBayes

public NaiveBayes()

Method Detail

load

public static NaiveBayes load(String path)

read

public static MLReader<T> read()

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

setSmoothing

public NaiveBayes setSmoothing(double value)

Set the smoothing parameter. Default is 1.0.

Parameters:

value - (undocumented)

Returns:

(undocumented)

setModelType

public NaiveBayes setModelType(String value)

Set the model type using a string (case-sensitive). Supported options: "multinomial" and "bernoulli". Default is "multinomial"

Parameters:

value - (undocumented)

Returns:

(undocumented)

setWeightCol

public NaiveBayes setWeightCol(String value)

Sets the value of param weightCol. If this is not set or empty, we treat all instance weights as 1.0. Default is not set, so all instances have weight one.

Parameters:

value - (undocumented)

Returns:

(undocumented)

copy

public NaiveBayes copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Predictor<Vector,NaiveBayes,NaiveBayesModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)