org.apache.spark.ml.clustering

Class GaussianMixtureModel

java.lang.Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.clustering.GaussianMixtureModel

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable, MLWritable

public class GaussianMixtureModel
extends Model<GaussianMixtureModel>
implements MLWritable

:: Experimental ::

Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points are drawn from each Gaussian i with probability weights(i).

param: weights Weight for each Gaussian distribution in the mixture. This is a multinomial probability distribution over the k Gaussians, where weights(i) is the weight for Gaussian i, and weights sum to 1. param: gaussians Array of MultivariateGaussian where gaussians(i) represents the Multivariate Gaussian (Normal) Distribution for Gaussian i

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
protected static <T> T	$(Param<T> param)
static Params	clear(Param<?> param)
GaussianMixtureModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
protected static <T extends Params> T	copyValues(T to, ParamMap extra)
protected static <T extends Params> ParamMap	copyValues$default$2()
protected static <T extends Params> T	defaultCopy(ParamMap extra)
static java.lang.String	explainParam(Param<?> param)
static java.lang.String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static Param<java.lang.String>	featuresCol()
MultivariateGaussian[]	gaussians()
Dataset<Row>	gaussiansDF() Retrieve Gaussian distributions as a DataFrame.
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static java.lang.String	getFeaturesCol()
static int	getK()
int	getK()
static int	getMaxIter()
static <T> T	getOrDefault(Param<T> param)
static Param<java.lang.Object>	getParam(java.lang.String paramName)
static java.lang.String	getPredictionCol()
static java.lang.String	getProbabilityCol()
static long	getSeed()
static double	getTol()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(java.lang.String paramName)
static boolean	hasParent()
boolean	hasSummary() Return true if there exists summary of model.
protected static void	initializeLogIfNecessary(boolean isInterpreter)
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
protected static boolean	isTraceEnabled()
static IntParam	k()
IntParam	k() Set the number of clusters to create (k).
static GaussianMixtureModel	load(java.lang.String path)
protected static org.slf4j.Logger	log()
protected static void	logDebug(scala.Function0<java.lang.String> msg)
protected static void	logDebug(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void	logError(scala.Function0<java.lang.String> msg)
protected static void	logError(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void	logInfo(scala.Function0<java.lang.String> msg)
protected static void	logInfo(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static java.lang.String	logName()
protected static void	logTrace(scala.Function0<java.lang.String> msg)
protected static void	logTrace(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
protected static void	logWarning(scala.Function0<java.lang.String> msg)
protected static void	logWarning(scala.Function0<java.lang.String> msg, java.lang.Throwable throwable)
static IntParam	maxIter()
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static Param<java.lang.String>	predictionCol()
static Param<java.lang.String>	probabilityCol()
static MLReader<GaussianMixtureModel>	read()
static void	save(java.lang.String path)
static LongParam	seed()
static <T> Params	set(Param<T> param, T value)
protected static Params	set(ParamPair<?> paramPair)
protected static Params	set(java.lang.String param, java.lang.Object value)
protected static <T> Params	setDefault(Param<T> param, T value)
protected static Params	setDefault(scala.collection.Seq<ParamPair<?>> paramPairs)
static M	setParent(Estimator<M> parent)
GaussianMixtureSummary	summary() Gets summary of model on training set.
static DoubleParam	tol()
static java.lang.String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
protected static StructType	validateAndTransformSchema(StructType schema)
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.
static void	validateParams()
double[]	weights()
MLWriter	write() Returns an MLWriter instance for this ML instance.

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

transformSchema

Methods inherited from class java.lang.Object

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

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, validateParams

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

toString

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

save

Method Detail

read

public static MLReader<GaussianMixtureModel> read()

load

public static GaussianMixtureModel load(java.lang.String path)

toString

public static java.lang.String toString()

params

public static Param<?>[] params()

validateParams

public static void validateParams()

explainParam

public static java.lang.String explainParam(Param<?> param)

explainParams

public static java.lang.String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(java.lang.String paramName)

getParam

public static Param<java.lang.Object> getParam(java.lang.String paramName)

set

public static final <T> Params set(Param<T> param,
             T value)

set

protected static final Params set(java.lang.String param,
         java.lang.Object value)

set

protected static final Params set(ParamPair<?> paramPair)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

$

protected static final <T> T $(Param<T> param)

setDefault

protected static final <T> Params setDefault(Param<T> param,
                    T value)

setDefault

protected static final Params setDefault(scala.collection.Seq<ParamPair<?>> paramPairs)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

defaultCopy

protected static final <T extends Params> T defaultCopy(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

copyValues

protected static <T extends Params> T copyValues(T to,
                              ParamMap extra)

copyValues$default$2

protected static <T extends Params> ParamMap copyValues$default$2()

logName

protected static java.lang.String logName()

log

protected static org.slf4j.Logger log()

logInfo

protected static void logInfo(scala.Function0<java.lang.String> msg)

logDebug

protected static void logDebug(scala.Function0<java.lang.String> msg)

logTrace

protected static void logTrace(scala.Function0<java.lang.String> msg)

logWarning

protected static void logWarning(scala.Function0<java.lang.String> msg)

logError

protected static void logError(scala.Function0<java.lang.String> msg)

logInfo

protected static void logInfo(scala.Function0<java.lang.String> msg,
           java.lang.Throwable throwable)

logDebug

protected static void logDebug(scala.Function0<java.lang.String> msg,
            java.lang.Throwable throwable)

logTrace

protected static void logTrace(scala.Function0<java.lang.String> msg,
            java.lang.Throwable throwable)

logWarning

protected static void logWarning(scala.Function0<java.lang.String> msg,
              java.lang.Throwable throwable)

logError

protected static void logError(scala.Function0<java.lang.String> msg,
            java.lang.Throwable throwable)

isTraceEnabled

protected static boolean isTraceEnabled()

initializeLogIfNecessary

protected static void initializeLogIfNecessary(boolean isInterpreter)

parent

public static Estimator<M> parent()

parent_$eq

public static void parent_$eq(Estimator<M> x$1)

setParent

public static M setParent(Estimator<M> parent)

hasParent

public static boolean hasParent()

maxIter

public static final IntParam maxIter()

getMaxIter

public static final int getMaxIter()

featuresCol

public static final Param<java.lang.String> featuresCol()

getFeaturesCol

public static final java.lang.String getFeaturesCol()

seed

public static final LongParam seed()

getSeed

public static final long getSeed()

predictionCol

public static final Param<java.lang.String> predictionCol()

getPredictionCol

public static final java.lang.String getPredictionCol()

probabilityCol

public static final Param<java.lang.String> probabilityCol()

getProbabilityCol

public static final java.lang.String getProbabilityCol()

tol

public static final DoubleParam tol()

getTol

public static final double getTol()

k

public static final IntParam k()

getK

public static int getK()

validateAndTransformSchema

protected static StructType validateAndTransformSchema(StructType schema)

save

public static void save(java.lang.String path)
                 throws java.io.IOException

Throws:

java.io.IOException

uid

public java.lang.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)

weights

public double[] weights()

gaussians

public MultivariateGaussian[] gaussians()

copy

public GaussianMixtureModel 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.

Specified by:

copy in interface Params

Specified by:

copy in class Model<GaussianMixtureModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

transform

public Dataset<Row> transform(Dataset<?> dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Derives the output schema from the input schema.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

gaussiansDF

public Dataset<Row> gaussiansDF()

Retrieve Gaussian distributions as a DataFrame. Each row represents a Gaussian Distribution. Two columns are defined: mean and cov. Schema:

  root
   |-- mean: vector (nullable = true)
   |-- cov: matrix (nullable = true)
 

Returns:

(undocumented)

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)

hasSummary

public boolean hasSummary()

Return true if there exists summary of model.

Returns:

(undocumented)

summary

public GaussianMixtureSummary summary()

Gets summary of model on training set. An exception is thrown if trainingSummary == None.

Returns:

(undocumented)

k

public IntParam k()

Set the number of clusters to create (k). Must be > 1. Default: 2.

Returns:

(undocumented)

getK

public int getK()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.

Parameters:

schema - input schema

Returns:

output schema