org.apache.spark.ml.classification

Class NaiveBayesModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.PredictionModel<FeaturesType,M>

org.apache.spark.ml.classification.ClassificationModel<FeaturesType,M>

org.apache.spark.ml.classification.ProbabilisticClassificationModel<Vector,NaiveBayesModel>

org.apache.spark.ml.classification.NaiveBayesModel

All Implemented Interfaces:

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

public class NaiveBayesModel
extends ProbabilisticClassificationModel<Vector,NaiveBayesModel>
implements NaiveBayesParams, MLWritable

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) param: sigma variance of each feature, whose dimension is C (number of classes) by D (number of features). This matrix is only available when modelType is set Gaussian.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Method Summary

Modifier and Type	Method and Description
NaiveBayesModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static NaiveBayesModel	load(String path)
Param<String>	modelType() The model type which is a string (case-sensitive).
int	numClasses() Number of classes (values which the label can take).
int	numFeatures() Returns the number of features the model was trained on.
Vector	pi()
Vector	predictRaw(Vector features) Raw prediction for each possible label.
static MLReader<NaiveBayesModel>	read()
Matrix	sigma()
DoubleParam	smoothing() The smoothing parameter.
Matrix	theta()
String	toString()
String	uid() An immutable unique ID for the object and its derivatives.
Param<String>	weightCol() Param for weight column name.
MLWriter	write() Returns an MLWriter instance for this ML instance.

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

normalizeToProbabilitiesInPlace, predictProbability, probabilityCol, setProbabilityCol, setThresholds, thresholds, transform, transformSchema

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

predict, rawPredictionCol, setRawPredictionCol, transformImpl

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

featuresCol, labelCol, predictionCol, setFeaturesCol, setPredictionCol

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

hasParent, parent, setParent

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

transform, transform, transform

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

params

Methods inherited from class Object

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

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

getModelType, getSmoothing

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, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

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

getWeightCol

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

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

getThresholds

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

$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Method Detail

read

public static MLReader<NaiveBayesModel> read()

load

public static NaiveBayesModel load(String path)

smoothing

public final DoubleParam smoothing()

Description copied from interface: NaiveBayesParams

The smoothing parameter. (default = 1.0).

Specified by:

smoothing in interface NaiveBayesParams

Returns:

(undocumented)

modelType

public final Param<String> modelType()

Description copied from interface: NaiveBayesParams

The model type which is a string (case-sensitive). Supported options: "multinomial", "complement", "bernoulli", "gaussian". (default = multinomial)

Specified by:

modelType in interface NaiveBayesParams

Returns:

(undocumented)

weightCol

public final Param<String> weightCol()

Description copied from interface: HasWeightCol

Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.

Specified by:

weightCol in interface HasWeightCol

Returns:

(undocumented)

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)

pi

public Vector pi()

theta

public Matrix theta()

sigma

public Matrix sigma()

numFeatures

public int numFeatures()

Description copied from class: PredictionModel

Returns the number of features the model was trained on. If unknown, returns -1

Overrides:

numFeatures in class PredictionModel<Vector,NaiveBayesModel>

numClasses

public int numClasses()

Description copied from class: ClassificationModel

Number of classes (values which the label can take).

Specified by:

numClasses in class ClassificationModel<Vector,NaiveBayesModel>

predictRaw

public Vector predictRaw(Vector features)

Description copied from class: ClassificationModel

Raw prediction for each possible label. The meaning of a "raw" prediction may vary between algorithms, but it intuitively gives a measure of confidence in each possible label (where larger = more confident). This internal method is used to implement transform() and output rawPredictionCol.

Specified by:

predictRaw in class ClassificationModel<Vector,NaiveBayesModel>

Parameters:

features - (undocumented)

Returns:

vector where element i is the raw prediction for label i. This raw prediction may be any real number, where a larger value indicates greater confidence for that label.

copy

public NaiveBayesModel 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 Model<NaiveBayesModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

toString

public String toString()

Specified by:

toString in interface Identifiable

Overrides:

toString in class Object

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)