edu.udo.cs.yale.operator.learner.meta
Class AdaBoost

java.lang.Object
  edu.udo.cs.yale.operator.Operator
      edu.udo.cs.yale.operator.OperatorChain
          edu.udo.cs.yale.operator.learner.meta.AbstractMetaLearner
              edu.udo.cs.yale.operator.learner.meta.AdaBoost

All Implemented Interfaces:

ConfigurationListener, Learner

public class AdaBoost
extends AbstractMetaLearner

This AdaBoost implementation can be used with all learners available in YALE, not only the ones which originally are part of the Weka package.

Version:

$Id: AdaBoost.java,v 1.13 2006/09/30 00:05:30 ingomierswa Exp $

Author:

Martin Scholz

Field Summary

protected int	currentIteration
static double	MIN_ADVANTAGE Discard models with an advantage of less than the specified value.
static java.lang.String	NUM_OF_ITERATIONS Name of the variable specifying the maximal number of iterations of the learner.
private double[]	oldWeights
private double	performance

Constructor Summary

AdaBoost(OperatorDescription description)
Constructor.

Method Summary

int	getNumberOfSteps() Returns the number of steps performed by this chain.
java.util.List<ParameterType>	getParameterTypes() Adds the parameters "number of iterations" and "model file".
private boolean	isModelUseful(AdaBoostPerformanceMeasures wp) Helper method to decide whether a model improves the training error enough to be considered.
Model	learn(ExampleSet exampleSet) Constructs a Model repeatedly running a weak learner, reweighting the training example set accordingly, and combining the hypothesis using the available weighted performance values.
protected double	prepareWeights(ExampleSet exampleSet) Creates a weight attribute if not yet done.
boolean	supportsCapability(LearnerCapability lc) Overrides the method of the super class.
private AdaBoostModel	trainBoostingModel(ExampleSet trainingSet) Main method for training the ensemble classifier

Methods inherited from class edu.udo.cs.yale.operator.learner.meta.AbstractMetaLearner

apply, applyInnerLearner, checkLearnerCapabilities, getEstimatedPerformance, getInnerOperatorCondition, getInputClasses, getInputDescription, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getOutputClasses, getWeights, shouldCalculateWeights, shouldEstimatePerformance, shouldReturnInnerOutput

Methods inherited from class edu.udo.cs.yale.operator.OperatorChain

addAddListener, addOperator, addOperator, checkDeprecations, checkIO, checkNumberOfInnerOperators, checkProperties, clearErrorList, clearStepCounter, cloneOperator, countStep, createExperimentTree, delete, experimentFinished, experimentStarts, getAllInnerOperators, getCurrentStep, getIndexOfOperator, getInnerOperatorForName, getInnerOperatorsXML, getNumberOfAllOperators, getNumberOfChildrensSteps, getNumberOfOperators, getOperator, getOperatorFromAll, getOperators, isEnabled, performAdditionalChecks, removeAddListener, removeOperator, setEnabled, setExperiment

Methods inherited from class edu.udo.cs.yale.operator.Operator

addError, addValue, addWarning, apply, createExperimentTree, createFromXML, createMarkedExperimentTree, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getErrorList, getExperiment, getInput, getInput, getInput, getIOContainerForInApplyLoopBreakpoint, getName, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsInt, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isParameterSet, logMessage, register, remove, rename, resume, setBreakpoint, setInput, setListParameter, setOperatorParameters, setParameter, setParameters, setParent, setUserDescription, toString, writeXML

Methods inherited from class java.lang.Object

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

Methods inherited from interface edu.udo.cs.yale.operator.learner.Learner

getName

Field Detail

NUM_OF_ITERATIONS

public static final java.lang.String NUM_OF_ITERATIONS

Name of the variable specifying the maximal number of iterations of the learner.

See Also:

Constant Field Values

MIN_ADVANTAGE

public static final double MIN_ADVANTAGE

Discard models with an advantage of less than the specified value.

See Also:

Constant Field Values

currentIteration

protected int currentIteration

performance

private double performance

oldWeights

private double[] oldWeights

Constructor Detail

AdaBoost

public AdaBoost(OperatorDescription description)

Constructor.

Method Detail

supportsCapability

public boolean supportsCapability(LearnerCapability lc)

Overrides the method of the super class. Returns true for polynominal class.

Specified by:

supportsCapability in interface Learner

Overrides:

supportsCapability in class AbstractMetaLearner

getNumberOfSteps

public int getNumberOfSteps()

Description copied from class: OperatorChain

Returns the number of steps performed by this chain.

Overrides:

getNumberOfSteps in class AbstractMetaLearner

See Also:

OperatorChain.getNumberOfSteps()

learn

public Model learn(ExampleSet exampleSet)
            throws OperatorException

Constructs a Model repeatedly running a weak learner, reweighting the training example set accordingly, and combining the hypothesis using the available weighted performance values.

Throws:

OperatorException

prepareWeights

protected double prepareWeights(ExampleSet exampleSet)

Creates a weight attribute if not yet done. It either backs up the old weights for restoring them later, or it fills the newly created attribute with the initial value of 1.

Parameters:

exampleSet - the example set to be prepared

Returns:

the total weight

trainBoostingModel

private AdaBoostModel trainBoostingModel(ExampleSet trainingSet)
                                  throws OperatorException

Main method for training the ensemble classifier

Throws:

OperatorException

isModelUseful

private boolean isModelUseful(AdaBoostPerformanceMeasures wp)

Helper method to decide whether a model improves the training error enough to be considered.

Parameters:

wp - the advantage over the default classifier / random guessing

Returns:

true iff the advantage is high enough to consider the model to be useful

getParameterTypes

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

Adds the parameters "number of iterations" and "model file".

Overrides:

getParameterTypes in class Operator