Package moa.evaluation

Class WindowRegressionPerformanceEvaluator

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.evaluation.WindowRegressionPerformanceEvaluator

All Implemented Interfaces:

Configurable, java.io.Serializable, CapabilitiesHandler, LearningPerformanceEvaluator<Example<Instance>>, RegressionPerformanceEvaluator, MOAObject, OptionHandler

public class WindowRegressionPerformanceEvaluator
extends AbstractOptionHandler
implements RegressionPerformanceEvaluator

Regression evaluator that updates evaluation results using a sliding window.

Version:

$Revision: 7 $

Author:

Albert Bifet (abifet at cs dot waikato dot ac dot nz)

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
class	WindowRegressionPerformanceEvaluator.Estimator

Field Summary

Fields

Modifier and Type	Field	Description
protected WindowRegressionPerformanceEvaluator.Estimator	averageError
protected int	numClasses
protected WindowRegressionPerformanceEvaluator.Estimator	squareError
protected double	TotalweightObserved
protected WindowRegressionPerformanceEvaluator.Estimator	weightObserved
IntOption	widthOption

Fields inherited from class moa.options.AbstractOptionHandler

config

Constructor Summary

Constructors

Constructor	Description
WindowRegressionPerformanceEvaluator()

Method Summary

Modifier and Type	Method	Description
void	addResult(Example<Instance> example, double[] prediction)	Adds a learning result to this evaluator.
void	addResult(Example<Instance> testInst, Prediction prediction)
void	getDescription(java.lang.StringBuilder sb, int indent)	Returns a string representation of this object.
double	getMeanError()
Measurement[]	getPerformanceMeasurements()	Gets the current measurements monitored by this evaluator.
double	getSquareError()
double	getTotalWeightObserved()
void	prepareForUseImpl(TaskMonitor monitor, ObjectRepository repository)	This method describes the implementation of how to prepare this object for use.
void	reset()	Resets this evaluator.
void	reset(int numClasses)

Methods inherited from class moa.AbstractMOAObject

copy, measureByteSize, measureByteSize, toString

Methods inherited from class moa.options.AbstractOptionHandler

copy, getCLICreationString, getOptions, getPreparedClassOption, getPurposeString, prepareClassOptions, prepareForUse, prepareForUse

Methods inherited from interface moa.capabilities.CapabilitiesHandler

getCapabilities

Methods inherited from interface moa.evaluation.LearningPerformanceEvaluator

defineImmutableCapabilities

Methods inherited from interface moa.MOAObject

copy, measureByteSize

Methods inherited from class java.lang.Object

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

Field Detail

widthOption

public IntOption widthOption

TotalweightObserved

protected double TotalweightObserved

weightObserved

protected WindowRegressionPerformanceEvaluator.Estimator weightObserved

squareError

protected WindowRegressionPerformanceEvaluator.Estimator squareError

averageError

protected WindowRegressionPerformanceEvaluator.Estimator averageError

numClasses

protected int numClasses

Constructor Detail

WindowRegressionPerformanceEvaluator

public WindowRegressionPerformanceEvaluator()

Method Detail

reset

public void reset()

Description copied from interface: LearningPerformanceEvaluator

Resets this evaluator. It must be similar to starting a new evaluator from scratch.

Specified by:

reset in interface LearningPerformanceEvaluator<Example<Instance>>

reset

public void reset(int numClasses)

addResult

public void addResult(Example<Instance> example,
                      double[] prediction)

Description copied from interface: LearningPerformanceEvaluator

Adds a learning result to this evaluator.

Specified by:

addResult in interface LearningPerformanceEvaluator<Example<Instance>>

Parameters:

example - the example to be classified

prediction - an array containing the estimated membership probabilities of the test instance in each class

getPerformanceMeasurements

public Measurement[] getPerformanceMeasurements()

Description copied from interface: LearningPerformanceEvaluator

Gets the current measurements monitored by this evaluator.

Specified by:

getPerformanceMeasurements in interface LearningPerformanceEvaluator<Example<Instance>>

Returns:

an array of measurements monitored by this evaluator

getTotalWeightObserved

public double getTotalWeightObserved()

getMeanError

public double getMeanError()

getSquareError

public double getSquareError()

getDescription

public void getDescription(java.lang.StringBuilder sb,
                           int indent)

Description copied from interface: MOAObject

Returns a string representation of this object. Used in AbstractMOAObject.toString to give a string representation of the object.

Specified by:

getDescription in interface MOAObject

Parameters:

sb - the stringbuilder to add the description

indent - the number of characters to indent

prepareForUseImpl

public void prepareForUseImpl(TaskMonitor monitor,
                              ObjectRepository repository)

Description copied from class: AbstractOptionHandler

This method describes the implementation of how to prepare this object for use. All classes that extends this class have to implement prepareForUseImpl and not prepareForUse since prepareForUse calls prepareForUseImpl.

Specified by:

prepareForUseImpl in class AbstractOptionHandler

Parameters:

monitor - the TaskMonitor to use

repository - the ObjectRepository to use

addResult

public void addResult(Example<Instance> testInst,
                      Prediction prediction)

Specified by:

addResult in interface LearningPerformanceEvaluator<Example<Instance>>