com.rapidminer.operator.clustering.clusterer
Class KernelKMeans

java.lang.Object
  com.rapidminer.operator.Operator
      com.rapidminer.operator.clustering.clusterer.AbstractClusterer
          com.rapidminer.operator.clustering.clusterer.KernelKMeans

All Implemented Interfaces:

ConfigurationListener, PreviewListener, ParameterHandler, LoggingHandler

public class KernelKMeans
extends AbstractClusterer

This operator is an implementation of kernel k means. Kernel K Means uses kernels to estimate distance between objects and clusters. Because of the nature of kernels it is necessary to sum over all elements of a cluster to calculate one distance. So this algorithm is quadratic in number of examples and returns NO CentroidClusterModel, as its older brother KMeans does. This operator will create a cluster attribute if not present yet.

Author:

Sebastian Land

Field Summary

static java.lang.String	PARAMETER_ADD_CLUSTER_ATTRIBUTE The parameter name for "Indicates if a cluster id is generated as new special attribute.
static java.lang.String	PARAMETER_K The parameter name for "the maximal number of clusters"
static java.lang.String	PARAMETER_LOCAL_RANDOM_SEED The parameter name for "Use the given random seed instead of global random numbers (-1: use global)"
static java.lang.String	PARAMETER_MAX_OPTIMIZATION_STEPS The parameter name for "the maximal number of iterations performed for one run of the k method"
static java.lang.String	PARAMETER_USE_WEIGHTS The parameter name for "the decision if exampleweights should be used "

Constructor Summary

KernelKMeans(OperatorDescription description)

Method Summary

ClusterModel	generateClusterModel(ExampleSet exampleSet) Generates a cluster model from an example set.
InputDescription	getInputDescription(java.lang.Class cls) Indicates that the consumption of example sets can be user defined.
java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.

Methods inherited from class com.rapidminer.operator.clustering.clusterer.AbstractClusterer

apply, getInputClasses, getOutputClasses

Methods inherited from class com.rapidminer.operator.Operator

addError, addValue, addWarning, apply, checkDeprecations, checkForStop, checkIO, checkProperties, clearErrorList, cloneOperator, createExperimentTree, createExperimentTree, createFromXML, createMarkedExperimentTree, createMarkedProcessTree, createProcessTree, createProcessTree, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getEncoding, getErrorList, getExperiment, getInnerOperatorsXML, getInput, getInput, getInput, getIOContainerForInApplyLoopBreakpoint, getIODescription, getLog, getName, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsFile, getParameterAsInputStream, getParameterAsInt, getParameterAsMatrix, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getProcess, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isDebugMode, isEnabled, isExpanded, isParallel, isParameterSet, log, logError, logNote, logWarning, performAdditionalChecks, processFinished, processStarts, register, registerOperator, remove, rename, resume, setApplyCount, setBreakpoint, setEnabled, setExpanded, setInput, setListParameter, setOperatorParameters, setParameter, setParameters, setParent, setUserDescription, toString, unregisterOperator, writeXML

Methods inherited from class java.lang.Object

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

Field Detail

PARAMETER_ADD_CLUSTER_ATTRIBUTE

public static final java.lang.String PARAMETER_ADD_CLUSTER_ATTRIBUTE

The parameter name for "Indicates if a cluster id is generated as new special attribute."

See Also:

Constant Field Values

PARAMETER_K

public static final java.lang.String PARAMETER_K

The parameter name for "the maximal number of clusters"

See Also:

Constant Field Values

PARAMETER_USE_WEIGHTS

public static final java.lang.String PARAMETER_USE_WEIGHTS

The parameter name for "the decision if exampleweights should be used "

See Also:

Constant Field Values

PARAMETER_MAX_OPTIMIZATION_STEPS

public static final java.lang.String PARAMETER_MAX_OPTIMIZATION_STEPS

The parameter name for "the maximal number of iterations performed for one run of the k method"

See Also:

Constant Field Values

PARAMETER_LOCAL_RANDOM_SEED

public static final java.lang.String PARAMETER_LOCAL_RANDOM_SEED

The parameter name for "Use the given random seed instead of global random numbers (-1: use global)"

See Also:

Constant Field Values

Constructor Detail

KernelKMeans

public KernelKMeans(OperatorDescription description)

Method Detail

generateClusterModel

public ClusterModel generateClusterModel(ExampleSet exampleSet)
                                  throws OperatorException

Description copied from class: AbstractClusterer

Generates a cluster model from an example set. Called by AbstractClusterer.apply().

Specified by:

generateClusterModel in class AbstractClusterer

Throws:

OperatorException

getParameterTypes

public java.util.List<ParameterType> getParameterTypes()

Description copied from class: Operator

Returns a list of ParameterTypes describing the parameters of this operator. The default implementation returns an empty list if no input objects can be retained and special parameters for those input objects which can be prevented from being consumed.

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class Operator

getInputDescription

public InputDescription getInputDescription(java.lang.Class cls)

Indicates that the consumption of example sets can be user defined.

Overrides:

getInputDescription in class Operator