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

java.lang.Object
  edu.udo.cs.yale.operator.AbstractIOObject
      edu.udo.cs.yale.operator.ResultObjectAdapter
          edu.udo.cs.yale.operator.AbstractModel
              edu.udo.cs.yale.operator.IOModel
                  edu.udo.cs.yale.operator.learner.PredictionModel
                      edu.udo.cs.yale.operator.learner.meta.AdaBoostModel

All Implemented Interfaces:

IOObject, Model, ResultObject, Saveable

public class AdaBoostModel
extends PredictionModel

A model for the Yale AdaBoost implementation.

Version:

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

Author:

Martin Scholz

Field Summary

static java.lang.String	ID
private static java.lang.String	MAX_MODEL_NUMBER
private int	maxModelNumber
private java.util.List<Model>	models
private java.util.List<java.lang.Double>	weights

Constructor Summary

AdaBoostModel()

AdaBoostModel(Attribute label)
Needed for creation of IOModel (when loading from file).

AdaBoostModel(Attribute label, java.util.List<Model> models, java.util.List<java.lang.Double> weights)

Method Summary

protected Attribute	createPredictedLabel(ExampleSet exampleSet) Creates a predicted label with the given name.
private void	evaluateSpecialAttributes(ExampleSet exampleSet, Attribute[] specialAttributes)
java.lang.String	getIdentifier()
Model	getModel(int index) Getter method for embedded models
int	getNumberOfModels()
private double	getWeightForModel(int modelNr)
void	performPrediction(ExampleSet origExampleSet, Attribute predictedLabel) Iterates over all models and returns the class with maximum likelihood.
void	readPredictionModelData(java.io.ObjectInputStream in) Reads all models from file.
void	setMaxModelNumber(int numModels) Using this setter with a positive value makes the model discard all but the specified number of base models.
void	setParameter(java.lang.String name, java.lang.String value) Setting the parameter MAX_MODEL_NUMBER allows to discard all but the first n models for specified n.
java.lang.String	toString()
private void	updateEstimates(ExampleSet exampleSet, int modelNr, Attribute[] specialAttributes)
void	writePredictionModelData(java.io.ObjectOutputStream out) Writes the models subsequently to the output stream.

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

apply, getLabel, readData, removePredictedLabel, setLabel, writeData

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

equals, getExtension, getFileDescription, readModel, readModel, save, setParameter, writeModel, writeModel

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

addAction, getActions, getName, getVisualisationComponent, toHTML, toResultString

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

copy, read, read, read, write, write

Methods inherited from class java.lang.Object

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

Methods inherited from interface edu.udo.cs.yale.operator.ResultObject

getActions, getName, getVisualisationComponent, toResultString

Methods inherited from interface edu.udo.cs.yale.operator.IOObject

copy, write, write

Field Detail

ID

public static final java.lang.String ID

See Also:

Constant Field Values

models

private java.util.List<Model> models

weights

private java.util.List<java.lang.Double> weights

maxModelNumber

private int maxModelNumber

MAX_MODEL_NUMBER

private static final java.lang.String MAX_MODEL_NUMBER

See Also:

Constant Field Values

Constructor Detail

AdaBoostModel

public AdaBoostModel()

AdaBoostModel

public AdaBoostModel(Attribute label)

Needed for creation of IOModel (when loading from file).

Parameters:

label - the class label

AdaBoostModel

public AdaBoostModel(Attribute label,
                     java.util.List<Model> models,
                     java.util.List<java.lang.Double> weights)

Method Detail

setParameter

public void setParameter(java.lang.String name,
                         java.lang.String value)
                  throws OperatorException

Setting the parameter MAX_MODEL_NUMBER allows to discard all but the first n models for specified n.

Throws:

OperatorException

setMaxModelNumber

public void setMaxModelNumber(int numModels)

Using this setter with a positive value makes the model discard all but the specified number of base models. A value of -1 turns off this option.

getIdentifier

public java.lang.String getIdentifier()

Returns:

the static class identifier of this model

readPredictionModelData

public void readPredictionModelData(java.io.ObjectInputStream in)
                             throws java.io.IOException

Reads all models from file.

Specified by:

readPredictionModelData in class PredictionModel

Throws:

java.io.IOException

writePredictionModelData

public void writePredictionModelData(java.io.ObjectOutputStream out)
                              throws java.io.IOException

Writes the models subsequently to the output stream.

Specified by:

writePredictionModelData in class PredictionModel

Throws:

java.io.IOException

toString

public java.lang.String toString()

Overrides:

toString in class PredictionModel

Returns:

a String representation of this boosting model.

getNumberOfModels

public int getNumberOfModels()

Returns:

the number of embedded models

getWeightForModel

private double getWeightForModel(int modelNr)

getModel

public Model getModel(int index)

Getter method for embedded models

Parameters:

index - the number of a model part of this boost model

Returns:

binary or nominal decision model

performPrediction

public void performPrediction(ExampleSet origExampleSet,
                              Attribute predictedLabel)
                       throws OperatorException

Iterates over all models and returns the class with maximum likelihood.

Specified by:

performPrediction in class PredictionModel

Parameters:

origExampleSet - the set of examples to be classified

Throws:

OperatorException

updateEstimates

private void updateEstimates(ExampleSet exampleSet,
                             int modelNr,
                             Attribute[] specialAttributes)

evaluateSpecialAttributes

private void evaluateSpecialAttributes(ExampleSet exampleSet,
                                       Attribute[] specialAttributes)

createPredictedLabel

protected Attribute createPredictedLabel(ExampleSet exampleSet)

Creates a predicted label with the given name. If name is null, the name "prediction(labelname)" is used.

Overrides:

createPredictedLabel in class PredictionModel