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

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.SDEnsemble

All Implemented Interfaces:

IOObject, Model, ResultObject, Saveable

public class SDEnsemble
extends PredictionModel

A subgroup discovery model.

Version:

$Id: SDEnsemble.java,v 1.26 2006/09/30 00:05:30 ingomierswa Exp $

Author:

Martin Scholz

Field Summary

private short	combinationMethod
static java.lang.String	ID
private static java.lang.String	MAX_MODEL_NUMBER
private int	maxModelNumber
private java.util.List	modelInfo
private static java.lang.String	PRED_TO_FILE
private java.io.File	predictionsFile
private boolean	print_to_stdout
private double[]	priors
static short	RULE_COMBINE_ADDITIVE
static short	RULE_COMBINE_MULTIPLY

Constructor Summary

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

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

SDEnsemble(Attribute label, java.util.List modelInfo, double[] priors, short combinationMethod)

Method Summary

protected Attribute	createPredictedLabel(ExampleSet exampleSet) Creates a predicted label with the given name.
java.lang.String	getIdentifier()
PredictionModel	getModel(int index) Getter method for embedded models
int	getNumberOfModels()
private double	getPriorOfClass(int classIndex) Getter method for prior class probabilities estimated as the relative frequencies in the training set.
private double[]	getWeightsForModel(int modelNr, int predicted) Gets weights for models in the case of general nominal class labels.
void	performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute) Iterates over all models and returns the class with maximum likelihood.
void	readPredictionModelData(java.io.ObjectInputStream in) Reads all models from file.
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()
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

RULE_COMBINE_ADDITIVE

public static final short RULE_COMBINE_ADDITIVE

See Also:

Constant Field Values

RULE_COMBINE_MULTIPLY

public static final short RULE_COMBINE_MULTIPLY

See Also:

Constant Field Values

combinationMethod

private short combinationMethod

modelInfo

private java.util.List modelInfo

maxModelNumber

private int maxModelNumber

MAX_MODEL_NUMBER

private static final java.lang.String MAX_MODEL_NUMBER

See Also:

Constant Field Values

PRED_TO_FILE

private static final java.lang.String PRED_TO_FILE

See Also:

Constant Field Values

predictionsFile

private java.io.File predictionsFile

print_to_stdout

private boolean print_to_stdout

priors

private double[] priors

Constructor Detail

SDEnsemble

public SDEnsemble()

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

SDEnsemble

public SDEnsemble(Attribute label)

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

Parameters:

label - the class label

SDEnsemble

public SDEnsemble(Attribute label,
                  java.util.List modelInfo,
                  double[] priors,
                  short combinationMethod)

Parameters:

label - the class label

modelInfo - a List of Object[2] arrays, each entry holding a model and a double[][] array containing weights for all prediction/label combinations.

priors - an array of the prior probabilities of labels

Method Detail

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 the ruleset.

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. PRED_TO_FILE requires a filename on the local disk system the predictions of the single classifiers are written to. print_to_stdout prints some statistics about the base classifiers to the standard output.

Throws:

OperatorException

getNumberOfModels

public int getNumberOfModels()

Returns:

the number of embedded models

getWeightsForModel

private double[] getWeightsForModel(int modelNr,
                                    int predicted)

Gets weights for models in the case of general nominal class labels. The indices are not in YALE format, so add Attribute.FIRST_CLASS_INDEX before calling this method and before reading from the returned array.

Parameters:

modelNr - the number of the model

predicted - the predicted label

Returns:

a double[] object with the weights to be applied for each class if the corresponding rule yields predicted.

getPriorOfClass

private double getPriorOfClass(int classIndex)

Getter method for prior class probabilities estimated as the relative frequencies in the training set.

Parameters:

classIndex - the index of a class starting with 0 (not the internal YALE representation!)

Returns:

the prior probability of the specified class

getModel

public PredictionModel 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 for the given classification index.

performPrediction

public void performPrediction(ExampleSet exampleSet,
                              Attribute predictedLabelAttribute)
                       throws OperatorException

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

Specified by:

performPrediction in class PredictionModel

Parameters:

exampleSet - the set of examples to be classified

Throws:

OperatorException

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