edu.udo.cs.yale.operator.learner.kernel
Class AbstractMySVMLearner

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

All Implemented Interfaces:

ConfigurationListener, Learner

Direct Known Subclasses:

JMySVMLearner, MyKLRLearner

public abstract class AbstractMySVMLearner
extends AbstractLearner

This is the abstract superclass for the support vector machine / KLR implementations of Stefan Rüping.

Version:

$Id: AbstractMySVMLearner.java,v 1.15 2006/03/27 13:22:01 ingomierswa Exp $

Author:

Ingo Mierswa

Keywords:

SVM

Field Summary

private Kernel	kernel The SVM kernel.
static int	KERNEL_DOT Indicates a linear kernel.
static int	KERNEL_EPANECHNIKOV Indicates a epanechnikov kernel.
static int	KERNEL_GAUSSIAN_COMBINATION Indicates a gaussian combination kernel.
static int	KERNEL_MULTIQUADRIC Indicates a multiquadric kernel.
static int	KERNEL_NEURAL Indicates a neural net kernel.
static int	KERNEL_POLYNOMIAL Indicates a polynomial kernel.
static int	KERNEL_RADIAL Indicates a rbf kernel.
static java.lang.String[]	KERNEL_TYPES The kernels which can be used from Yale for the mySVM / myKLR.
private SVMInterface	svm The SVM which is used for learning.
private ExampleSet	svmExamples The SVM example set.

Constructor Summary

AbstractMySVMLearner(OperatorDescription description)

Method Summary

static Kernel	createKernel(int kernelType) Creates a new kernel of the given type.
abstract SVMInterface	createSVM(Attribute label, Kernel kernel, ExampleSet svmExamples, ExampleSet yaleExamples) Creates a new SVM according to the given label.
abstract AbstractMySVMModel	createSVMModel(Attribute label, ExampleSet svmExamples, Kernel kernel, int kernelType) Creates a new SVM model from the given data.
private double	getFitness(double[] alphas, double[] ys, Kernel kernel)
protected Kernel	getKernel() Returns the kernel of this SVM.
PerformanceVector	getOptimizationPerformance() Returns the optimization performance of the best result.
java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.
protected SVMInterface	getSVM() Returns the used SVM.
AttributeWeights	getWeights(ExampleSet exampleSet) Returns the weights for all features.
Model	learn(ExampleSet exampleSet) Trains a model.
boolean	shouldCalculateWeights() Returns true if the user has specified that weights should be calculated.
boolean	shouldDeliverOptimizationPerformance() Returns the value of the corresponding parameter.

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

apply, checkLearnerCapabilities, getEstimatedPerformance, getInputClasses, getInputDescription, getOutputClasses, 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, supportsCapability

Field Detail

KERNEL_TYPES

public static final java.lang.String[] KERNEL_TYPES

The kernels which can be used from Yale for the mySVM / myKLR.

KERNEL_DOT

public static final int KERNEL_DOT

Indicates a linear kernel.

See Also:

Constant Field Values

KERNEL_RADIAL

public static final int KERNEL_RADIAL

Indicates a rbf kernel.

See Also:

Constant Field Values

KERNEL_POLYNOMIAL

public static final int KERNEL_POLYNOMIAL

Indicates a polynomial kernel.

See Also:

Constant Field Values

KERNEL_NEURAL

public static final int KERNEL_NEURAL

Indicates a neural net kernel.

See Also:

Constant Field Values

KERNEL_EPANECHNIKOV

public static final int KERNEL_EPANECHNIKOV

Indicates a epanechnikov kernel.

See Also:

Constant Field Values

KERNEL_GAUSSIAN_COMBINATION

public static final int KERNEL_GAUSSIAN_COMBINATION

Indicates a gaussian combination kernel.

See Also:

Constant Field Values

KERNEL_MULTIQUADRIC

public static final int KERNEL_MULTIQUADRIC

Indicates a multiquadric kernel.

See Also:

Constant Field Values

svm

private SVMInterface svm

The SVM which is used for learning.

kernel

private Kernel kernel

The SVM kernel.

svmExamples

private ExampleSet svmExamples

The SVM example set.

Constructor Detail

AbstractMySVMLearner

public AbstractMySVMLearner(OperatorDescription description)

Method Detail

getKernel

protected Kernel getKernel()

Returns the kernel of this SVM.

getSVM

protected SVMInterface getSVM()

Returns the used SVM.

shouldDeliverOptimizationPerformance

public boolean shouldDeliverOptimizationPerformance()

Returns the value of the corresponding parameter.

Overrides:

shouldDeliverOptimizationPerformance in class AbstractLearner

getOptimizationPerformance

public PerformanceVector getOptimizationPerformance()

Returns the optimization performance of the best result. This method must be called after training, not before.

Overrides:

getOptimizationPerformance in class AbstractLearner

shouldCalculateWeights

public boolean shouldCalculateWeights()

Returns true if the user has specified that weights should be calculated.

Specified by:

shouldCalculateWeights in interface Learner

Overrides:

shouldCalculateWeights in class AbstractLearner

getWeights

public AttributeWeights getWeights(ExampleSet exampleSet)
                            throws OperatorException

Returns the weights for all features.

Specified by:

getWeights in interface Learner

Overrides:

getWeights in class AbstractLearner

Throws:

OperatorException

createSVM

public abstract SVMInterface createSVM(Attribute label,
                                       Kernel kernel,
                                       ExampleSet svmExamples,
                                       ExampleSet yaleExamples)
                                throws OperatorException

Creates a new SVM according to the given label.

Throws:

OperatorException

createSVMModel

public abstract AbstractMySVMModel createSVMModel(Attribute label,
                                                  ExampleSet svmExamples,
                                                  Kernel kernel,
                                                  int kernelType)

Creates a new SVM model from the given data.

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

getFitness

private double getFitness(double[] alphas,
                          double[] ys,
                          Kernel kernel)

createKernel

public static Kernel createKernel(int kernelType)

Creates a new kernel of the given type. The kernel type has to be one out of KERNEL_DOT, KERNEL_RADIAL, KERNEL_POLYNOMIAL, KERNEL_NEURAL, KERNEL_EPANECHNIKOV, KERNEL_GAUSSIAN_COMBINATION, or KERNEL_MULTIQUADRIC.

getParameterTypes

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

Description copied from class: Operator

Returns a list of ParameterTypes describing the parameters of this operator. The default implementation returns an empty list if no input objects can be retained and special parameters for those input objects which can be prevented from being consumed.

Overrides:

getParameterTypes in class Operator