org.apache.spark.ml.clustering

Class BisectingKMeansModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.clustering.BisectingKMeansModel

All Implemented Interfaces:

java.io.Serializable, Params, Identifiable, MLWritable

public class BisectingKMeansModel
extends Model<BisectingKMeansModel>
implements MLWritable

:: Experimental :: Model fitted by BisectingKMeans.

param: parentModel a model trained by BisectingKMeans.

See Also:

Serialized Form

Method Summary

Methods

Modifier and Type	Method and Description
static Params	clear(Param<?> param)
Vector[]	clusterCenters()
double	computeCost(Dataset<?> dataset) Computes the sum of squared distances between the input points and their corresponding cluster centers.
BisectingKMeansModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static String	explainParam(Param<?> param)
static String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static Param<String>	featuresCol()
static <T> scala.Option<T>	get(Param<T> param)
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getFeaturesCol()
static int	getK()
int	getK()
static int	getMaxIter()
static double	getMinDivisibleClusterSize()
double	getMinDivisibleClusterSize()
static <T> T	getOrDefault(Param<T> param)
static Param<Object>	getParam(String paramName)
static String	getPredictionCol()
static long	getSeed()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static boolean	hasParent()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
static IntParam	k()
IntParam	k() The desired number of leaf clusters.
static BisectingKMeansModel	load(String path)
static IntParam	maxIter()
static DoubleParam	minDivisibleClusterSize()
DoubleParam	minDivisibleClusterSize() The minimum number of points (if >= 1.0) or the minimum proportion of points (if < 1.0) of a divisible cluster (default: 1.0).
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
static Param<String>	predictionCol()
static MLReader<BisectingKMeansModel>	read()
static void	save(String path)
static LongParam	seed()
static <T> Params	set(Param<T> param, T value)
static M	setParent(Estimator<M> parent)
static String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.
StructType	validateAndTransformSchema(StructType schema) Validates and transforms the input schema.
static void	validateParams()
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 Object

equals, 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<BisectingKMeansModel> read()

load

public static BisectingKMeansModel load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

validateParams

public static void validateParams()

explainParam

public static String explainParam(Param<?> param)

explainParams

public static String explainParams()

isSet

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

isDefined

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

hasParam

public static boolean hasParam(String paramName)

getParam

public static Param<Object> getParam(String paramName)

set

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

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)

getDefault

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

hasDefault

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

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

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<String> featuresCol()

getFeaturesCol

public static final String getFeaturesCol()

seed

public static final LongParam seed()

getSeed

public static final long getSeed()

predictionCol

public static final Param<String> predictionCol()

getPredictionCol

public static final String getPredictionCol()

k

public static final IntParam k()

getK

public static int getK()

minDivisibleClusterSize

public static final DoubleParam minDivisibleClusterSize()

getMinDivisibleClusterSize

public static double getMinDivisibleClusterSize()

save

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

Throws:

java.io.IOException

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)

copy

public BisectingKMeansModel 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<BisectingKMeansModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

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 ::

Check transform validity and derive the output schema from the input schema.

Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

clusterCenters

public Vector[] clusterCenters()

computeCost

public double computeCost(Dataset<?> dataset)

Computes the sum of squared distances between the input points and their corresponding cluster centers.

Parameters:

dataset - (undocumented)

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)

k

public IntParam k()

The desired number of leaf clusters. Must be > 1. Default: 4. The actual number could be smaller if there are no divisible leaf clusters.

Returns:

(undocumented)

getK

public int getK()

minDivisibleClusterSize

public DoubleParam minDivisibleClusterSize()

The minimum number of points (if >= 1.0) or the minimum proportion of points (if < 1.0) of a divisible cluster (default: 1.0).

Returns:

(undocumented)

getMinDivisibleClusterSize

public double getMinDivisibleClusterSize()

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema)

Validates and transforms the input schema.

Parameters:

schema - input schema

Returns:

output schema