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

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

All Implemented Interfaces:

ConfigurationListener, Learner

public class MyKLRLearner
extends AbstractMySVMLearner

This is the Java implementation of myKLR by Stefan Rüping. myKLR is a tool for large scale kernel logistic regression based on the algorithm of Keerthi/etal/2003 and the code of mySVM.

Version:

$Id: MyKLRLearner.java,v 1.13 2006/08/03 14:39:31 ingomierswa Exp $

Author:

Ingo Mierswa

Keywords:

KLR

Field Summary

Fields inherited from class edu.udo.cs.yale.operator.learner.kernel.AbstractMySVMLearner

KERNEL_DOT, KERNEL_EPANECHNIKOV, KERNEL_GAUSSIAN_COMBINATION, KERNEL_MULTIQUADRIC, KERNEL_NEURAL, KERNEL_POLYNOMIAL, KERNEL_RADIAL, KERNEL_TYPES

Constructor Summary

MyKLRLearner(OperatorDescription description)

Method Summary

SVMInterface	createSVM(Attribute label, Kernel kernel, ExampleSet exampleSet, ExampleSet yaleExamples) Creates a new SVM according to the given label.
AbstractMySVMModel	createSVMModel(Attribute label, ExampleSet exampleSet, Kernel kernel, int kernelType) Creates a new SVM model from the given data.
boolean	supportsCapability(LearnerCapability lc) Checks for Learner capabilities.

Methods inherited from class edu.udo.cs.yale.operator.learner.kernel.AbstractMySVMLearner

createKernel, getKernel, getOptimizationPerformance, getParameterTypes, getSVM, getWeights, learn, shouldCalculateWeights, shouldDeliverOptimizationPerformance

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

Constructor Detail

MyKLRLearner

public MyKLRLearner(OperatorDescription description)

Method Detail

supportsCapability

public boolean supportsCapability(LearnerCapability lc)

Description copied from interface: Learner

Checks for Learner capabilities. Should return true if the given capability is supported.

createSVMModel

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

Description copied from class: AbstractMySVMLearner

Creates a new SVM model from the given data.

Specified by:

createSVMModel in class AbstractMySVMLearner

createSVM

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

Description copied from class: AbstractMySVMLearner

Creates a new SVM according to the given label.

Specified by:

createSVM in class AbstractMySVMLearner

Throws:

OperatorException