edu.udo.cs.yale.operator.learner
Class MultiCriterionDecisionStumps

java.lang.Object
  edu.udo.cs.yale.operator.Operator
      edu.udo.cs.yale.operator.learner.AbstractLearner
          edu.udo.cs.yale.operator.learner.MultiCriterionDecisionStumps

All Implemented Interfaces:

ConfigurationListener, Learner

public class MultiCriterionDecisionStumps
extends AbstractLearner

A DecisionStump clone that allows to specify different utility functions. It is quick for nominal attributes, but does not yet apply pruning for continuos attributes. Currently it can only handle boolean class labels.

Version:

$Id: MultiCriterionDecisionStumps.java,v 1.6 2006/09/30 00:05:31 ingomierswa Exp $

Author:

Martin Scholz

Nested Class Summary

class	MultiCriterionDecisionStumps.DecisionStumpModel
private class	MultiCriterionDecisionStumps.ScoreNaNInfo

Field Summary

private static java.lang.String	ACC
private Model	bestModel
private double	bestScore
private static java.lang.String	CHI_SQUARE
private static java.lang.String	ENTROPY
private static java.lang.String	GINI
private double	globalN
private double	globalP
private int	posIndex
private static java.lang.String	SQRT_PN
private static java.lang.String	UTILITY_FUNCTION
private static java.lang.String[]	UTILITY_FUNCTION_LIST
private java.lang.String	utilityFunction

Constructor Summary

MultiCriterionDecisionStumps(OperatorDescription description)

Method Summary

protected double[]	computePriors(ExampleSet exampleSet)
private double	entropyLog2(double p)
private void	evaluateNominalAttributes(ExampleSet exampleSet)
private void	evaluateNumericalAttributes(ExampleSet exampleSet)
protected Model	getBestModel()
java.util.List<ParameterType>	getParameterTypes() Adds the parameter function".
protected double	getScore(double[] counts, boolean predictPositives) Computes the score for the specified utility function, the provided counts and class.
private MultiCriterionDecisionStumps.ScoreNaNInfo	getScore(double[] counts, double[] countNaNs)
protected void	initHighscore()
Model	learn(ExampleSet exampleSet) Trains a model.
private void	setBestModel(MultiCriterionDecisionStumps.DecisionStumpModel model, double score)
boolean	supportsCapability(LearnerCapability lc) Checks for Learner capabilities.

Methods inherited from class edu.udo.cs.yale.operator.learner.AbstractLearner

apply, checkLearnerCapabilities, getEstimatedPerformance, getInputClasses, getInputDescription, getOptimizationPerformance, getOutputClasses, getWeights, shouldCalculateWeights, shouldDeliverOptimizationPerformance, shouldEstimatePerformance

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

addError, addValue, addWarning, apply, checkDeprecations, checkIO, checkProperties, clearErrorList, cloneOperator, createExperimentTree, createExperimentTree, createFromXML, createMarkedExperimentTree, delete, experimentFinished, experimentStarts, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getErrorList, getExperiment, getInnerOperatorsXML, getInput, getInput, getInput, getIOContainerForInApplyLoopBreakpoint, getName, getNumberOfSteps, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsInt, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isEnabled, isParameterSet, logMessage, performAdditionalChecks, register, remove, rename, resume, setBreakpoint, setEnabled, setExperiment, 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

ACC

private static final java.lang.String ACC

See Also:

Constant Field Values

ENTROPY

private static final java.lang.String ENTROPY

See Also:

Constant Field Values

SQRT_PN

private static final java.lang.String SQRT_PN

See Also:

Constant Field Values

GINI

private static final java.lang.String GINI

See Also:

Constant Field Values

CHI_SQUARE

private static final java.lang.String CHI_SQUARE

See Also:

Constant Field Values

UTILITY_FUNCTION_LIST

private static final java.lang.String[] UTILITY_FUNCTION_LIST

UTILITY_FUNCTION

private static final java.lang.String UTILITY_FUNCTION

See Also:

Constant Field Values

posIndex

private int posIndex

globalP

private double globalP

globalN

private double globalN

bestModel

private Model bestModel

bestScore

private double bestScore

utilityFunction

private java.lang.String utilityFunction

Constructor Detail

MultiCriterionDecisionStumps

public MultiCriterionDecisionStumps(OperatorDescription description)

Method Detail

supportsCapability

public boolean supportsCapability(LearnerCapability lc)

Description copied from interface: Learner

Checks for Learner capabilities. Should return true if the given capability is supported.

initHighscore

protected void initHighscore()

getBestModel

protected Model getBestModel()

Returns:

the best decision stump found

setBestModel

private void setBestModel(MultiCriterionDecisionStumps.DecisionStumpModel model,
                          double score)

learn

public Model learn(ExampleSet exampleSet)
            throws OperatorException

Description copied from interface: Learner

Trains a model. This method should be called by apply() and is implemented by subclasses.

Throws:

OperatorException

evaluateNumericalAttributes

private void evaluateNumericalAttributes(ExampleSet exampleSet)
                                  throws OperatorException

Throws:

OperatorException

evaluateNominalAttributes

private void evaluateNominalAttributes(ExampleSet exampleSet)
                                throws OperatorException

Throws:

OperatorException

getScore

private MultiCriterionDecisionStumps.ScoreNaNInfo getScore(double[] counts,
                                                           double[] countNaNs)
                                                    throws UndefinedParameterError

Throws:

UndefinedParameterError

getScore

protected double getScore(double[] counts,
                          boolean predictPositives)

Computes the score for the specified utility function, the provided counts and class.

entropyLog2

private double entropyLog2(double p)

computePriors

protected double[] computePriors(ExampleSet exampleSet)

Parameters:

exampleSet - the exampleSet to get the weighted priors for

Returns:

a double[2] object, first parameter is p, second is n.

getParameterTypes

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

Adds the parameter &utility function".

Overrides:

getParameterTypes in class Operator