Package adams.ml.model.clustering

Class WekaClusterer

java.lang.Object

adams.core.logging.LoggingObject

adams.core.logging.CustomLoggingLevelObject

adams.core.option.AbstractOptionHandler

adams.ml.model.clustering.AbstractClusterer

adams.ml.model.clustering.WekaClusterer

All Implemented Interfaces:

Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, SizeOfHandler, CapabilitiesHandler, Algorithm<ClusteringModel>, Clusterer, Serializable

public class WekaClusterer
extends AbstractClusterer

Wraps around a Weka clusterer.

-logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> (property: loggingLevel)
    The logging level for outputting errors and debugging output.
    default: WARNING
 

-strict-capabilities <boolean> (property: strictCapabilities)
    If enabled, a strict capabilities test is performed; otherwise, it is attempted 
    to adjust the data to fit the algorithm's capabilities.
    default: false
 

-clusterer <weka.clusterers.Clusterer> (property: clusterer)
    The clusterer to use.
    default: weka.clusterers.SimpleKMeans -init 0 -max-candidates 100 -periodic-pruning 10000 -min-density 2.0 -t1 -1.25 -t2 -1.0 -N 2 -A \"weka.core.EuclideanDistance -R first-last\" -I 500 -num-slots 1 -S 10
 

Version:

$Revision$

Author:

FracPete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected weka.clusterers.Clusterer	m_Clusterer	the weka classifier to use.

Fields inherited from class adams.ml.model.clustering.AbstractClusterer

m_StrictCapabilities

Fields inherited from class adams.core.option.AbstractOptionHandler

m_OptionManager

Fields inherited from class adams.core.logging.LoggingObject

m_Logger, m_LoggingIsEnabled, m_LoggingLevel

Constructor Summary

Constructors

Constructor	Description
WekaClusterer()

Method Summary

Modifier and Type	Method	Description
String	clustererTipText()	Returns the tip text for this property.
void	defineOptions()	Adds options to the internal list of options.
protected ClusteringModel	doBuildModel(Dataset data)	Builds a model from the data.
Capabilities	getCapabilities()	Returns the algorithm's capabilities in terms of data.
weka.clusterers.Clusterer	getClusterer()	Returns the clusterer to use.
String	globalInfo()	Returns a string describing the object.
void	setClusterer(weka.clusterers.Clusterer value)	Sets the clusterer to use.

Methods inherited from class adams.ml.model.clustering.AbstractClusterer

buildModel, check, getStrictCapabilities, handles, setStrictCapabilities, strictCapabilitiesTipText

Methods inherited from class adams.core.option.AbstractOptionHandler

cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, initialize, loggingLevelTipText, newOptionManager, reset, setLoggingLevel, toCommandLine, toString

Methods inherited from class adams.core.logging.LoggingObject

configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf

Methods inherited from class java.lang.Object

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

Methods inherited from interface adams.core.Destroyable

destroy

Methods inherited from interface adams.core.logging.LoggingLevelHandler

getLoggingLevel

Methods inherited from interface adams.core.option.OptionHandler

cleanUpOptions, getOptionManager, toCommandLine

Field Detail

m_Clusterer

protected weka.clusterers.Clusterer m_Clusterer

the weka classifier to use.

Constructor Detail

WekaClusterer

public WekaClusterer()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing the object.

Specified by:

globalInfo in interface GlobalInfoSupporter

Specified by:

globalInfo in class AbstractOptionHandler

Returns:

a description suitable for displaying in the gui

defineOptions

public void defineOptions()

Adds options to the internal list of options.

Specified by:

defineOptions in interface OptionHandler

Overrides:

defineOptions in class AbstractClusterer

setClusterer

public void setClusterer(weka.clusterers.Clusterer value)

Sets the clusterer to use.

Parameters:

value - the clusterer

getClusterer

public weka.clusterers.Clusterer getClusterer()

Returns the clusterer to use.

Returns:

the clusterer

clustererTipText

public String clustererTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

getCapabilities

public Capabilities getCapabilities()

Returns the algorithm's capabilities in terms of data.

Specified by:

getCapabilities in interface Algorithm<ClusteringModel>

Specified by:

getCapabilities in interface CapabilitiesHandler

Overrides:

getCapabilities in class AbstractClusterer

Returns:

the algorithm's capabilities

doBuildModel

protected ClusteringModel doBuildModel(Dataset data)
                                throws Exception

Builds a model from the data.

Specified by:

doBuildModel in class AbstractClusterer

Parameters:

data - the data to use for building the model

Returns:

the generated model

Throws:

Exception - if the build fails