weka.knowledgeflow.steps

Class Clusterer

java.lang.Object

weka.knowledgeflow.steps.BaseStep

weka.knowledgeflow.steps.WekaAlgorithmWrapper

weka.knowledgeflow.steps.Clusterer

All Implemented Interfaces:

java.io.Serializable, BaseStepExtender, PairedDataHelper.PairedProcessor<Clusterer>, Step

@KFStep(name="Clusterer",
        category="Clusterers",
        toolTipText="Weka clusterer wrapper",
        iconPath="",
        resourceIntensive=true)
public class Clusterer
extends WekaAlgorithmWrapper
implements PairedDataHelper.PairedProcessor<Clusterer>

Step that wraps a Weka clusterer. Handles trainingSet and testSet incoming connections

Version:

$Revision: $

Author:

Mark Hall (mhall{[at]}pentaho{[dot]}com)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
Clusterer()

Method Summary

Modifier and Type	Method and Description
Clusterer	getClusterer() Get the clusterer to train
java.util.List<java.lang.String>	getIncomingConnectionTypes() Get a list of connection types that could be made to this Step at this point in time
java.io.File	getLoadClustererFileName() Get the name of the clusterer to load at execution time.
java.util.List<java.lang.String>	getOutgoingConnectionTypes() Get a list of outgoing connections that could be made from this step at this point in time
java.lang.Class	getWrappedAlgorithmClass() Get the class of the wrapped algorithm
void	processIncoming(Data data) Process an incoming data object
Clusterer	processPrimary(java.lang.Integer setNum, java.lang.Integer maxSetNum, Data data, PairedDataHelper<Clusterer> helper) Process a training split (primary data handled by the PairedDataHelper)
void	processSecondary(java.lang.Integer setNum, java.lang.Integer maxSetNum, Data data, PairedDataHelper<Clusterer> helper) Process a test split/fold (secondary data handled by PairedDataHelper)
void	setClusterer(Clusterer clusterer) Set the clusterer to train
void	setLoadClustererFileName(java.io.File filename) Set the name of the clusterer to load at execution time.
void	setWrappedAlgorithm(java.lang.Object algo) Set the wrapped algorithm
void	stepInit() Initialize the step

Methods inherited from class weka.knowledgeflow.steps.WekaAlgorithmWrapper

getDefaultIconPath, getDefaultPackageLevelIconPath, getIconPath, getWrappedAlgorithm, globalInfo

Methods inherited from class weka.knowledgeflow.steps.BaseStep

environmentSubstitute, getCustomEditorForStep, getDefaultSettings, getInteractiveViewers, getInteractiveViewersImpls, getName, getStepManager, isResourceIntensive, isStopRequested, outputStructureForConnectionType, outputStructureForConnectionType, setName, setStepIsResourceIntensive, setStepManager, setStepMustRunSingleThreaded, start, stepMustRunSingleThreaded, stop

Methods inherited from class java.lang.Object

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

Constructor Detail

Clusterer

public Clusterer()

Method Detail

getClusterer

public Clusterer getClusterer()

Get the clusterer to train

Returns:

the clusterer to train

setClusterer

@ProgrammaticProperty
public void setClusterer(Clusterer clusterer)

Set the clusterer to train

Parameters:

clusterer - the clusterer to train

getLoadClustererFileName

public java.io.File getLoadClustererFileName()

Get the name of the clusterer to load at execution time. This only applies in the case where the only incoming connection is a test set connection (batch mode) or an instance connection (incremental prediction mode).

Returns:

the name of the file to load the model from

setLoadClustererFileName

@OptionMetadata(displayName="Clusterer model to load",
                description="Optional path to a clusterer to load at execution time (only applies when using testSet connections)")
 @FilePropertyMetadata(fileChooserDialogType=0,
                      directoriesOnly=false)
public void setLoadClustererFileName(java.io.File filename)

Set the name of the clusterer to load at execution time. This only applies in the case where the only incoming connection is a test set connection (batch mode) or an instance connection (incremental prediction mode).

Parameters:

filename - the name of the file to load the model from

getWrappedAlgorithmClass

public java.lang.Class getWrappedAlgorithmClass()

Get the class of the wrapped algorithm

Specified by:

getWrappedAlgorithmClass in class WekaAlgorithmWrapper

Returns:

the class of the wrapped algorithm

setWrappedAlgorithm

public void setWrappedAlgorithm(java.lang.Object algo)

Set the wrapped algorithm

Overrides:

setWrappedAlgorithm in class WekaAlgorithmWrapper

Parameters:

algo - the algorithm to wrap

stepInit

public void stepInit()
              throws WekaException

Initialize the step

Specified by:

stepInit in interface BaseStepExtender

Specified by:

stepInit in interface Step

Throws:

WekaException - if a problem occurs

processIncoming

public void processIncoming(Data data)
                     throws WekaException

Process an incoming data object

Specified by:

processIncoming in interface BaseStepExtender

Specified by:

processIncoming in interface Step

Overrides:

processIncoming in class BaseStep

Parameters:

data - the data to process

Throws:

WekaException - if a problem occurs

getIncomingConnectionTypes

public java.util.List<java.lang.String> getIncomingConnectionTypes()

Get a list of connection types that could be made to this Step at this point in time

Specified by:

getIncomingConnectionTypes in interface BaseStepExtender

Specified by:

getIncomingConnectionTypes in interface Step

Returns:

a list of incoming connection types that could be made at this time

getOutgoingConnectionTypes

public java.util.List<java.lang.String> getOutgoingConnectionTypes()

Get a list of outgoing connections that could be made from this step at this point in time

Specified by:

getOutgoingConnectionTypes in interface BaseStepExtender

Specified by:

getOutgoingConnectionTypes in interface Step

Returns:

a list of outgoing connections that could be made at this point in time

processPrimary

public Clusterer processPrimary(java.lang.Integer setNum,
                                java.lang.Integer maxSetNum,
                                Data data,
                                PairedDataHelper<Clusterer> helper)
                         throws WekaException

Process a training split (primary data handled by the PairedDataHelper)

Specified by:

processPrimary in interface PairedDataHelper.PairedProcessor<Clusterer>

Parameters:

setNum - the number of this split/fold

maxSetNum - the maximum number of splits/folds in the group

data - the actual split/fold data

helper - the PairedDataHelper managing the paired data

Returns:

a Classifier trained on this training split

Throws:

WekaException - if a problem occurs

processSecondary

public void processSecondary(java.lang.Integer setNum,
                             java.lang.Integer maxSetNum,
                             Data data,
                             PairedDataHelper<Clusterer> helper)
                      throws WekaException

Process a test split/fold (secondary data handled by PairedDataHelper)

Specified by:

processSecondary in interface PairedDataHelper.PairedProcessor<Clusterer>

Parameters:

setNum - the set number of this split/fold

maxSetNum - the maximum number of splits/folds in the group

data - the actual split/fold data

helper - the PairedDataHelper managing the paried data

Throws:

WekaException - if a problem occurs