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, Logging, BisectingKMeansParams, Params, HasDistanceMeasure, HasFeaturesCol, HasMaxIter, HasPredictionCol, HasSeed, Identifiable, MLWritable

public class BisectingKMeansModel
extends Model<BisectingKMeansModel>
implements BisectingKMeansParams, MLWritable

Model fitted by BisectingKMeans.

param: parentModel a model trained by BisectingKMeans.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
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.
boolean	hasSummary() Return true if there exists summary of model.
static BisectingKMeansModel	load(String path)
static MLReader<BisectingKMeansModel>	read()
BisectingKMeansModel	setFeaturesCol(String value)
BisectingKMeansModel	setPredictionCol(String value)
BisectingKMeansSummary	summary() Gets summary of model on training set.
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.
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.clustering.BisectingKMeansParams

getK, getMinDivisibleClusterSize, k, minDivisibleClusterSize, validateAndTransformSchema

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

getMaxIter, maxIter

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

featuresCol, getFeaturesCol

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

getSeed, seed

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

getPredictionCol, predictionCol

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

distanceMeasure, getDistanceMeasure

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.util.MLWritable

save

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

Method Detail

read

public static MLReader<BisectingKMeansModel> read()

load

public static BisectingKMeansModel load(String path)

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)

setFeaturesCol

public BisectingKMeansModel setFeaturesCol(String value)

setPredictionCol

public BisectingKMeansModel setPredictionCol(String value)

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.

We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

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)

hasSummary

public boolean hasSummary()

Return true if there exists summary of model.

Returns:

(undocumented)

summary

public BisectingKMeansSummary summary()

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

Returns:

(undocumented)