adams.flow.transformer
Class MOAClustererEvaluation

java.lang.Object
  adams.core.ConsoleObject
      adams.core.option.AbstractOptionHandler
          adams.flow.core.AbstractActor
              adams.flow.transformer.AbstractTransformer
                  adams.flow.transformer.MOAClustererEvaluation

All Implemented Interfaces:

AdditionalInformationHandler, CleanUpHandler, Debuggable, DebugOutputHandler, Destroyable, OptionHandler, QuickInfoSupporter, ShallowCopySupporter<AbstractActor>, SizeOfHandler, Stoppable, VariableChangeListener, Actor, ErrorHandler, InputConsumer, OutputProducer, Serializable, Comparable

public class MOAClustererEvaluation
extends AbstractTransformer

Evaluates a MOA clusterer using prequential evaluation. With each incoming instance, the clusterer is first evaluated, then trained.

Input/output:
- accepts:
weka.core.Instance
- generates:
moa.core.Measurement[]

Valid options are:

-D <int> (property: debugLevel)
    The greater the number the more additional info the scheme may output to
    the console (0 = off).
    default: 0
    minimum: 0
 

-name <java.lang.String> (property: name)
    The name of the actor.
    default: MOAClustererEvaluation
 

-annotation <adams.core.base.BaseText> (property: annotations)
    The annotations to attach to this actor.
    default:
 

-skip (property: skip)
    If set to true, transformation is skipped and the input token is just forwarded
    as it is.
 

-stop-flow-on-error (property: stopFlowOnError)
    If set to true, the flow gets stopped in case this actor encounters an error;
     useful for critical actors.
 

-clusterer <java.lang.String> (property: clusterer)
    The name of the global MOA clusterer to train/evaluate.
    default: MOAClusterer
 

-evaluator <moa.options.ClassOption> (property: evaluator)
    The MOA evaluator to use for evaluating a trained MOA clusterer.
    default: moa.evaluation.BasicClusteringPerformanceEvaluator
 

-output-interval <int> (property: outputInterval)
    The number of tokens to skip before evaluating the clusterer stored in the
    token.
    default: 1
    minimum: 1
 

Version:

$Revision: 6830 $

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

static String	BACKUP_CLUSTERER the key for storing the current clusterer in the backup.
protected moa.clusterers.AbstractClusterer	m_ActualClusterer the model to use for prediction/training.
protected moa.evaluation.LearningPerformanceEvaluator	m_ActualEvaluator the actual evaluator to use.
protected GlobalActorReference	m_Clusterer the name of the global clusterer to use.
protected int	m_Count the current count of tokens that have passed through this actor.
protected moa.options.ClassOption	m_Evaluator the evaluation to use.
protected int	m_OutputInterval the output interval.

Fields inherited from class adams.flow.transformer.AbstractTransformer

BACKUP_INPUT, BACKUP_OUTPUT, m_InputToken, m_OutputToken

Fields inherited from class adams.flow.core.AbstractActor

m_Annotations, m_BackupState, m_DetectedObjectVariables, m_DetectedVariables, m_ErrorHandler, m_Executed, m_Executing, m_ExecutionListeningSupporter, m_FullName, m_Headless, m_Name, m_Parent, m_Root, m_ScopeHandler, m_Self, m_Skip, m_StopFlowOnError, m_StopMessage, m_Stopped, m_StorageHandler, m_VariablesUpdated

Fields inherited from class adams.core.option.AbstractOptionHandler

m_DebugLevel, m_OptionManager

Fields inherited from interface adams.flow.core.Actor

FILE_EXTENSION, FILE_EXTENSION_GZ

Constructor Summary

MOAClustererEvaluation()

Method Summary

Class[]	accepts() Returns the class that the consumer accepts.
protected Hashtable<String,Object>	backupState() Backs up the current state of the actor before update the variables.
String	clustererTipText() Returns the tip text for this property.
void	defineOptions() Adds options to the internal list of options.
protected String	doExecute() Executes the flow item.
String	evaluatorTipText() Returns the tip text for this property.
Class[]	generates() Returns the class of objects that it generates.
GlobalActorReference	getClusterer() Returns the global clusterer to use.
protected moa.clusterers.AbstractClusterer	getClustererInstance() Returns an instance of the global clusterer.
protected moa.evaluation.LearningPerformanceEvaluator	getCurrentEvaluator() Returns the current evaluator, based on the class option.
protected moa.evaluation.LearningPerformanceEvaluator	getDefaultEvaluator() Returns the default evaluator.
protected moa.options.ClassOption	getDefaultOption() Returns the default class option.
moa.options.ClassOption	getEvaluator() Returns the evaluator in use.
int	getOutputInterval() Returns the number of tokens after which to evaluate the clusterer.
String	getQuickInfo() Returns a quick info about the actor, which will be displayed in the GUI.
String	globalInfo() Returns a string describing the object.
String	outputIntervalTipText() Returns the tip text for this property.
protected void	pruneBackup() Removes entries from the backup.
protected void	reset() Initializes the members.
protected void	restoreState(Hashtable<String,Object> state) Restores the state of the actor before the variables got updated.
void	setClusterer(GlobalActorReference value) Sets the global clusterer to use.
void	setEvaluator(moa.options.ClassOption value) Sets the evaluator to use.
void	setOutputInterval(int value) Sets the number of tokens after which to evaluate the clusterer.
void	updateProvenance(ProvenanceContainer cont) Updates the provenance information in the provided container.
void	wrapUp() Cleans up after the execution has finished.

Methods inherited from class adams.flow.transformer.AbstractTransformer

execute, hasPendingOutput, input, output, postExecute

Methods inherited from class adams.flow.core.AbstractActor

annotationsTipText, canInspectOptions, canPerformSetUpCheck, cleanUp, compareTo, debug, destroy, equals, findVariables, findVariables, findVariables, forceVariables, forCommandLine, forName, getAdditionalInformation, getAnnotations, getDefaultName, getDetectedVariables, getErrorHandler, getFlowActors, getFlowExecutionListeningSupporter, getFullName, getName, getNextSibling, getParent, getParentComponent, getPreviousSibling, getRoot, getScopeHandler, getSkip, getStopFlowOnError, getStopMessage, getStorageHandler, getVariables, handleError, handleException, hasErrorHandler, hasStopMessage, index, initialize, isBackedUp, isExecuted, isExecuting, isFinished, isHeadless, isStopped, nameTipText, performSetUpChecks, preExecute, pruneBackup, setAnnotations, setErrorHandler, setHeadless, setName, setParent, setSkip, setStopFlowOnError, setUp, setVariables, shallowCopy, shallowCopy, sizeOf, skipTipText, stopExecution, stopExecution, stopFlowOnErrorTipText, updateDetectedVariables, updatePrefix, updateVariables, variableChanged

Methods inherited from class adams.core.option.AbstractOptionHandler

cleanUpOptions, debug, debugLevelTipText, finishInit, getDebugLevel, getOptionManager, isDebugOn, newOptionManager, setDebugLevel, toCommandLine, toString

Methods inherited from class adams.core.ConsoleObject

getDebugging, getSystemErr, getSystemOut

Methods inherited from class java.lang.Object

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

Methods inherited from interface adams.flow.core.Actor

cleanUp, compareTo, debug, destroy, equals, findVariables, getAnnotations, getDefaultName, getDetectedVariables, getErrorHandler, getFlowExecutionListeningSupporter, getFullName, getName, getNextSibling, getParent, getParentComponent, getPreviousSibling, getRoot, getScopeHandler, getSkip, getStopFlowOnError, getStopMessage, getStorageHandler, getVariables, handleError, hasErrorHandler, hasStopMessage, index, isExecuted, isFinished, isHeadless, isStopped, setAnnotations, setErrorHandler, setHeadless, setName, setParent, setSkip, setStopFlowOnError, setUp, setVariables, sizeOf, stopExecution, stopExecution, variableChanged

Methods inherited from interface adams.core.AdditionalInformationHandler

getAdditionalInformation

Methods inherited from interface adams.core.option.OptionHandler

cleanUpOptions, getOptionManager

Field Detail

BACKUP_CLUSTERER

public static final String BACKUP_CLUSTERER

the key for storing the current clusterer in the backup.

See Also:

Constant Field Values

m_Clusterer

protected GlobalActorReference m_Clusterer

the name of the global clusterer to use.

m_ActualClusterer

protected moa.clusterers.AbstractClusterer m_ActualClusterer

the model to use for prediction/training.

m_Evaluator

protected moa.options.ClassOption m_Evaluator

the evaluation to use.

m_ActualEvaluator

protected moa.evaluation.LearningPerformanceEvaluator m_ActualEvaluator

the actual evaluator to use.

m_OutputInterval

protected int m_OutputInterval

the output interval.

m_Count

protected int m_Count

the current count of tokens that have passed through this actor.

Constructor Detail

MOAClustererEvaluation

public MOAClustererEvaluation()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing the object.

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 AbstractActor

reset

protected void reset()

Initializes the members.

Overrides:

reset in class AbstractTransformer

setClusterer

public void setClusterer(GlobalActorReference value)

Sets the global clusterer to use.

Parameters:

value - the clusterer name

getClusterer

public GlobalActorReference getClusterer()

Returns the global clusterer to use.

Returns:

the clusterer name

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.

getDefaultEvaluator

protected moa.evaluation.LearningPerformanceEvaluator getDefaultEvaluator()

Returns the default evaluator.

Returns:

the evaluator

getDefaultOption

protected moa.options.ClassOption getDefaultOption()

Returns the default class option.

Returns:

the option

setEvaluator

public void setEvaluator(moa.options.ClassOption value)

Sets the evaluator to use.

Parameters:

value - the evaluator

getEvaluator

public moa.options.ClassOption getEvaluator()

Returns the evaluator in use.

Returns:

the evaluator

evaluatorTipText

public String evaluatorTipText()

Returns the tip text for this property.

Returns:

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

getCurrentEvaluator

protected moa.evaluation.LearningPerformanceEvaluator getCurrentEvaluator()

Returns the current evaluator, based on the class option.

Returns:

the evaluator

See Also:

getEvaluator()

setOutputInterval

public void setOutputInterval(int value)

Sets the number of tokens after which to evaluate the clusterer.

Parameters:

value - the interval

getOutputInterval

public int getOutputInterval()

Returns the number of tokens after which to evaluate the clusterer.

Returns:

the interval

outputIntervalTipText

public String outputIntervalTipText()

Returns the tip text for this property.

Returns:

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

getQuickInfo

public String getQuickInfo()

Returns a quick info about the actor, which will be displayed in the GUI.

Specified by:

getQuickInfo in interface QuickInfoSupporter

Specified by:

getQuickInfo in interface Actor

Overrides:

getQuickInfo in class AbstractActor

Returns:

null if no info available, otherwise short string

accepts

public Class[] accepts()

Returns the class that the consumer accepts.

Returns:

weka.core.Instance.class

generates

public Class[] generates()

Returns the class of objects that it generates.

Returns:

moa.core.Measurement[].class

pruneBackup

protected void pruneBackup()

Removes entries from the backup.

Overrides:

pruneBackup in class AbstractActor

backupState

protected Hashtable<String,Object> backupState()

Backs up the current state of the actor before update the variables.

Overrides:

backupState in class AbstractTransformer

Returns:

the backup

restoreState

protected void restoreState(Hashtable<String,Object> state)

Restores the state of the actor before the variables got updated.

Overrides:

restoreState in class AbstractTransformer

Parameters:

state - the backup of the state to restore from

getClustererInstance

protected moa.clusterers.AbstractClusterer getClustererInstance()

Returns an instance of the global clusterer.

Returns:

the clusterer

doExecute

protected String doExecute()

Executes the flow item.

Specified by:

doExecute in class AbstractActor

Returns:

null if everything is fine, otherwise error message

updateProvenance

public void updateProvenance(ProvenanceContainer cont)

Updates the provenance information in the provided container.

Parameters:

cont - the provenance container to update

wrapUp

public void wrapUp()

Cleans up after the execution has finished.

Specified by:

wrapUp in interface Actor

Overrides:

wrapUp in class AbstractTransformer