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

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

All Implemented Interfaces:

IOObject, Model, ResultObject, Saveable

Direct Known Subclasses:

AdaBoostModel, AverageModel, BaggingModel, BayBoostModel, DefaultModel, GSSModel, KernelModel, MultiModel, MultiModelByRegression, ParetoOptimalSetOfModels, PlattScalingModel, SDEnsemble, SimpleBinaryPredictionModel, SimplePredictionModel, TransformedRegressionModel, WekaClassifier

public abstract class PredictionModel
extends IOModel

PredictionModel is the superclass for all objects generated by learners, i.e. it can be used to create a prediction for a given example set. Please note that each subclass must provide a zero-argument constructor in order to allow model creation by reflection.

Version:

$Id: PredictionModel.java,v 2.8 2006/08/03 14:39:34 ingomierswa Exp $

Author:

Ingo Mierswa

Field Summary

private Attribute

label We remember the target attribute in order to be able to create predicted label attributes based on this type.

Constructor Summary

protected	PredictionModel() Invokes the super constructor.
protected	PredictionModel(Attribute label)

Method Summary

void	apply(ExampleSet exampleSet) Applies the model by creating a predicted label attribue and setting the predicted label values.
protected Attribute	createPredictedLabel(ExampleSet exampleSet) Creates a predicted label for the given example set based on the label attribute defined for this prediction model.
Attribute	getLabel() Returns the label attribute.
abstract void	performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Subclasses should iterated through the given example set and set the prediction for each example.
void	readData(java.io.ObjectInputStream in) Reads the label information and creates a label attribute.
abstract void	readPredictionModelData(java.io.ObjectInputStream in) Reads the model data (without label).
static void	removePredictedLabel(ExampleSet exampleSet) Helper method in order to lower memory consumption.
void	setLabel(Attribute label) Sets the label attribute.
java.lang.String	toString()
void	writeData(java.io.ObjectOutputStream out) Writes the label information.
abstract void	writePredictionModelData(java.io.ObjectOutputStream out) Writes the model data (without label).

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

label

private transient Attribute label

We remember the target attribute in order to be able to create predicted label attributes based on this type. It is declared transient since we handle serialization of the attribute ourselves.

Constructor Detail

PredictionModel

protected PredictionModel()

Invokes the super constructor. This method is needed during creation by reflection.

PredictionModel

protected PredictionModel(Attribute label)

Method Detail

performPrediction

public abstract void performPrediction(ExampleSet exampleSet,
                                       Attribute predictedLabel)
                                throws OperatorException

Subclasses should iterated through the given example set and set the prediction for each example. The given predicted label attribute was already be added to the example set and should be used to set the predicted values.

Throws:

OperatorException

readPredictionModelData

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

Reads the model data (without label).

Throws:

java.io.IOException

writePredictionModelData

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

Writes the model data (without label).

Throws:

java.io.IOException

readData

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

Reads the label information and creates a label attribute. Afterwards, the remaining model data should be read by invoking the abstract method readPredictionModelData(ObjectInputStream).

Specified by:

readData in class IOModel

Throws:

java.io.IOException

writeData

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

Writes the label information. Afterwards, the remaining model data should be written by invoking the abstract method writePredictionModelData(ObjectOutputStream).

Specified by:

writeData in class AbstractModel

Throws:

java.io.IOException

apply

public void apply(ExampleSet exampleSet)
           throws OperatorException

Applies the model by creating a predicted label attribue and setting the predicted label values.

Throws:

OperatorException

setLabel

public void setLabel(Attribute label)

Sets the label attribute.

getLabel

public Attribute getLabel()

Returns the label attribute.

createPredictedLabel

protected Attribute createPredictedLabel(ExampleSet exampleSet)

Creates a predicted label for the given example set based on the label attribute defined for this prediction model. Subclasses which override this method should first invoke super.createPredictedLabel(exampleSet) and should then replace the attribute with a new predicted label attribute via a method call like exampleSet.replaceAttribute(predictedLabel, AttributeFactory.changeValueType(predictedLabel, Ontology.REAL)); . This might be usefull in cases where a crisp nominal prediction should be replace by confidence predictions.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

removePredictedLabel

public static void removePredictedLabel(ExampleSet exampleSet)

Helper method in order to lower memory consumption. This method should be invoked after a predicted label and confidence are not longer needed, e.g. after each crossvalidation run or after a meta learning iteration.