com.rapidminer.operator.learner.functions.kernel
Class AbstractMySVMModel

java.lang.Object
  com.rapidminer.operator.AbstractIOObject
      com.rapidminer.operator.ResultObjectAdapter
          com.rapidminer.operator.AbstractModel
              com.rapidminer.operator.learner.PredictionModel
                  com.rapidminer.operator.learner.functions.kernel.KernelModel
                      com.rapidminer.operator.learner.functions.kernel.AbstractMySVMModel

All Implemented Interfaces:

IOObject, FormulaProvider, Model, ResultObject, Saveable, Readable, Reportable, LoggingHandler, java.io.Serializable

Direct Known Subclasses:

JMySVMModel, MyKLRModel

public abstract class AbstractMySVMModel
extends KernelModel
implements FormulaProvider

The abstract superclass for the SVM models by Stefan Rueping.

Author:

Ingo Mierswa

See Also:

Serialized Form

Constructor Summary

AbstractMySVMModel(ExampleSet exampleSet, SVMExamples model, Kernel kernel, int kernelType)

Method Summary

abstract SVMInterface	createSVM() Creates a new SVM for prediction.
double	getAlpha(int index)
double	getAttributeValue(int exampleIndex, int attributeIndex)
double	getBias()
java.lang.String	getClassificationLabel(int index)
SVMExamples	getExampleSet() Gets the model, i.e. an SVM example set.
java.lang.String	getFormula()
double	getFunctionValue(int index)
java.lang.String	getId(int index)
Kernel	getKernel() Gets the kernel.
int	getNumberOfAttributes()
int	getNumberOfSupportVectors()
double	getRegressionLabel(int index)
SupportVector	getSupportVector(int index) This method must divide the alpha by the label since internally the alpha value is already multiplied with y.
boolean	isClassificationModel()
ExampleSet	performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute) Subclasses should iterate through the given example set and set the prediction for each example.
abstract void	setPrediction(Example example, double prediction) Sets the correct prediction to the example from the result value of the SVM.

Methods inherited from class com.rapidminer.operator.learner.functions.kernel.KernelModel

createWeightsTable, getAttributeConstructions, getName, getVisualizationComponent, toString

Methods inherited from class com.rapidminer.operator.learner.PredictionModel

apply, checkCompatibility, copyPredictedLabel, createPredictedLabel, getLabel, removePredictedLabel, removePredictedLabel

Methods inherited from class com.rapidminer.operator.AbstractModel

getExtension, getFileDescription, getResultIcon, getTrainingHeader, isUpdatable, setParameter, updateModel

Methods inherited from class com.rapidminer.operator.ResultObjectAdapter

addAction, getActions, isSavable, log, logError, logNote, logWarning, save, toHTML, toResultString

Methods inherited from class com.rapidminer.operator.AbstractIOObject

copy, getLog, getSource, initWriting, read, setLoggingHandler, setSource, write

Methods inherited from class java.lang.Object

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

Methods inherited from interface com.rapidminer.operator.Model

apply, isUpdatable, setParameter, updateModel

Methods inherited from interface com.rapidminer.operator.ResultObject

getActions, getName, getResultIcon, getVisualizationComponent, toResultString

Methods inherited from interface com.rapidminer.operator.IOObject

copy, getLog, getSource, setLoggingHandler, setSource, write

Methods inherited from interface com.rapidminer.operator.Saveable

getExtension, getFileDescription, isSavable, save

Methods inherited from interface com.rapidminer.report.Readable

toString

Constructor Detail

AbstractMySVMModel

public AbstractMySVMModel(ExampleSet exampleSet,
                          SVMExamples model,
                          Kernel kernel,
                          int kernelType)

Method Detail

createSVM

public abstract SVMInterface createSVM()

Creates a new SVM for prediction.

isClassificationModel

public boolean isClassificationModel()

Specified by:

isClassificationModel in class KernelModel

getBias

public double getBias()

Specified by:

getBias in class KernelModel

getSupportVector

public SupportVector getSupportVector(int index)

This method must divide the alpha by the label since internally the alpha value is already multiplied with y.

Specified by:

getSupportVector in class KernelModel

getAlpha

public double getAlpha(int index)

Specified by:

getAlpha in class KernelModel

getId

public java.lang.String getId(int index)

Specified by:

getId in class KernelModel

getNumberOfSupportVectors

public int getNumberOfSupportVectors()

Specified by:

getNumberOfSupportVectors in class KernelModel

getNumberOfAttributes

public int getNumberOfAttributes()

Specified by:

getNumberOfAttributes in class KernelModel

getAttributeValue

public double getAttributeValue(int exampleIndex,
                                int attributeIndex)

Specified by:

getAttributeValue in class KernelModel

getClassificationLabel

public java.lang.String getClassificationLabel(int index)

Specified by:

getClassificationLabel in class KernelModel

getRegressionLabel

public double getRegressionLabel(int index)

Specified by:

getRegressionLabel in class KernelModel

getFunctionValue

public double getFunctionValue(int index)

Specified by:

getFunctionValue in class KernelModel

getKernel

public Kernel getKernel()

Gets the kernel.

getExampleSet

public SVMExamples getExampleSet()

Gets the model, i.e. an SVM example set.

setPrediction

public abstract void setPrediction(Example example,
                                   double prediction)

Sets the correct prediction to the example from the result value of the SVM.

performPrediction

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

Description copied from class: PredictionModel

Subclasses should iterate 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.

Specified by:

performPrediction in class PredictionModel

Throws:

OperatorException

getFormula

public java.lang.String getFormula()

Specified by:

getFormula in interface FormulaProvider