com.rapidminer.operator.learner.functions.kernel.evosvm
Class EvoSVM

java.lang.Object
  com.rapidminer.operator.Operator
      com.rapidminer.operator.learner.AbstractLearner
          com.rapidminer.operator.learner.functions.kernel.evosvm.EvoSVM

All Implemented Interfaces:

ConfigurationListener, PreviewListener, Learner, ParameterHandler, LoggingHandler

public class EvoSVM
extends AbstractLearner

This is a SVM implementation using an evolutionary algorithm (ES) to solve the dual optimization problem of a SVM. It turns out that on many datasets this simple implementation is as fast and accurate as the usual SVM implementations. In addition, it is also capable of learning with Kernels which are not positive semi-definite and can also be used for multi-objective learning which makes the selection of C unecessary before learning.

Mierswa, Ingo. Evolutionary Learning with Kernels: A Generic Solution for Large Margin Problems. In Proc. of the Genetic and Evolutionary Computation Conference (GECCO 2006), 2006.

Author:

Ingo Mierswa

Keywords:

SVM

Field Summary

static java.lang.String	PARAMETER_C The parameter name for "The SVM complexity constant (0: calculates probably good value).
static java.lang.String	PARAMETER_CROSSOVER_PROB The parameter name for "The probability for crossovers.
static java.lang.String	PARAMETER_EPSILON The parameter name for "The width of the regression tube loss function of the regression SVM"
static java.lang.String	PARAMETER_GENERATIONS_WITHOUT_IMPROVAL The parameter name for "Stop after this number of generations without improvement (-1: optimize until max_iterations).
static java.lang.String	PARAMETER_HOLD_OUT_SET_RATIO The parameter name for "Uses this amount as a hold out set to estimate generalization error after learning (currently only used for multi-objective classification).
static java.lang.String	PARAMETER_KEEP_BEST The parameter name for "Indicates if the best individual should survive (elititst selection).
static java.lang.String	PARAMETER_MAX_GENERATIONS The parameter name for "Stop after this many evaluations"
static java.lang.String	PARAMETER_MUTATION_TYPE The parameter name for "The type of the mutation operator.
static java.lang.String	PARAMETER_POPULATION_SIZE The parameter name for "The population size (-1: number of examples)"
static java.lang.String	PARAMETER_RETURN_OPTIMIZATION_PERFORMANCE The parameter name for "Indicates if final optimization fitness should be returned as performance.
static java.lang.String	PARAMETER_SELECTION_TYPE The parameter name for "The type of the selection operator.
static java.lang.String	PARAMETER_SHOW_CONVERGENCE_PLOT The parameter name for "Indicates if a dialog with a convergence plot should be drawn.
static java.lang.String	PARAMETER_SHOW_POPULATION_PLOT
static java.lang.String	PARAMETER_START_POPULATION_TYPE The parameter name for "The type of start population initialization.
static java.lang.String	PARAMETER_TOURNAMENT_FRACTION The parameter name for "The fraction of the population used for tournament selection.

Fields inherited from class com.rapidminer.operator.learner.AbstractLearner

PROPERTY_RAPIDMINER_GENERAL_CAPABILITIES_WARN

Constructor Summary

EvoSVM(OperatorDescription description)
Creates a new SVM which uses an Evolutionary Strategy approach for optimization.

Method Summary

static double[]	createBoundArray(double bound, int size)
static double[]	determineMax(double _c, Kernel kernel, ExampleSet exampleSet, int selectionType, int arraySize)
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.
Model	learn(ExampleSet exampleSet) Learns and returns a model.
boolean	shouldDeliverOptimizationPerformance() Returns the value of the corresponding parameter.
boolean	supportsCapability(LearnerCapability lc) Returns true for numerical attributes, binominal classes, and numerical target attributes.

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

apply, getEstimatedPerformance, getInputClasses, getInputDescription, getOutputClasses, getWeights, onlyWarnForNonSufficientCapabilities, shouldCalculateWeights, shouldEstimatePerformance

Methods inherited from class com.rapidminer.operator.Operator

addError, addValue, addWarning, apply, checkDeprecations, checkForStop, checkIO, checkProperties, clearErrorList, cloneOperator, createExperimentTree, createExperimentTree, createFromXML, createMarkedExperimentTree, createMarkedProcessTree, createProcessTree, createProcessTree, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getEncoding, getErrorList, getExperiment, getInnerOperatorsXML, getInput, getInput, getInput, getIOContainerForInApplyLoopBreakpoint, getIODescription, getLog, getName, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsFile, getParameterAsInputStream, getParameterAsInt, getParameterAsMatrix, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getProcess, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isDebugMode, isEnabled, isExpanded, isParallel, isParameterSet, log, logError, logNote, logWarning, performAdditionalChecks, processFinished, processStarts, register, registerOperator, remove, rename, resume, setApplyCount, setBreakpoint, setEnabled, setExpanded, setInput, setListParameter, setOperatorParameters, setParameter, setParameters, setParent, setUserDescription, toString, unregisterOperator, writeXML

Methods inherited from class java.lang.Object

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

Methods inherited from interface com.rapidminer.operator.learner.Learner

getName

Field Detail

PARAMETER_C

public static final java.lang.String PARAMETER_C

The parameter name for "The SVM complexity constant (0: calculates probably good value)."

See Also:

Constant Field Values

PARAMETER_EPSILON

public static final java.lang.String PARAMETER_EPSILON

The parameter name for "The width of the regression tube loss function of the regression SVM"

See Also:

Constant Field Values

PARAMETER_START_POPULATION_TYPE

public static final java.lang.String PARAMETER_START_POPULATION_TYPE

The parameter name for "The type of start population initialization."

See Also:

Constant Field Values

PARAMETER_MAX_GENERATIONS

public static final java.lang.String PARAMETER_MAX_GENERATIONS

The parameter name for "Stop after this many evaluations"

See Also:

Constant Field Values

PARAMETER_GENERATIONS_WITHOUT_IMPROVAL

public static final java.lang.String PARAMETER_GENERATIONS_WITHOUT_IMPROVAL

The parameter name for "Stop after this number of generations without improvement (-1: optimize until max_iterations)."

See Also:

Constant Field Values

PARAMETER_POPULATION_SIZE

public static final java.lang.String PARAMETER_POPULATION_SIZE

The parameter name for "The population size (-1: number of examples)"

See Also:

Constant Field Values

PARAMETER_TOURNAMENT_FRACTION

public static final java.lang.String PARAMETER_TOURNAMENT_FRACTION

The parameter name for "The fraction of the population used for tournament selection."

See Also:

Constant Field Values

PARAMETER_KEEP_BEST

public static final java.lang.String PARAMETER_KEEP_BEST

The parameter name for "Indicates if the best individual should survive (elititst selection)."

See Also:

Constant Field Values

PARAMETER_MUTATION_TYPE

public static final java.lang.String PARAMETER_MUTATION_TYPE

The parameter name for "The type of the mutation operator."

See Also:

Constant Field Values

PARAMETER_SELECTION_TYPE

public static final java.lang.String PARAMETER_SELECTION_TYPE

The parameter name for "The type of the selection operator."

See Also:

Constant Field Values

PARAMETER_CROSSOVER_PROB

public static final java.lang.String PARAMETER_CROSSOVER_PROB

The parameter name for "The probability for crossovers."

See Also:

Constant Field Values

PARAMETER_HOLD_OUT_SET_RATIO

public static final java.lang.String PARAMETER_HOLD_OUT_SET_RATIO

The parameter name for "Uses this amount as a hold out set to estimate generalization error after learning (currently only used for multi-objective classification)."

See Also:

Constant Field Values

PARAMETER_SHOW_CONVERGENCE_PLOT

public static final java.lang.String PARAMETER_SHOW_CONVERGENCE_PLOT

The parameter name for "Indicates if a dialog with a convergence plot should be drawn."

See Also:

Constant Field Values

PARAMETER_SHOW_POPULATION_PLOT

public static final java.lang.String PARAMETER_SHOW_POPULATION_PLOT

See Also:

Constant Field Values

PARAMETER_RETURN_OPTIMIZATION_PERFORMANCE

public static final java.lang.String PARAMETER_RETURN_OPTIMIZATION_PERFORMANCE

The parameter name for "Indicates if final optimization fitness should be returned as performance."

See Also:

Constant Field Values

Constructor Detail

EvoSVM

public EvoSVM(OperatorDescription description)

Creates a new SVM which uses an Evolutionary Strategy approach for optimization.

Method Detail

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

learn

public Model learn(ExampleSet exampleSet)
            throws OperatorException

Learns and returns a model.

Throws:

OperatorException

supportsCapability

public boolean supportsCapability(LearnerCapability lc)

Returns true for numerical attributes, binominal classes, and numerical target attributes.

createBoundArray

public static double[] createBoundArray(double bound,
                                        int size)

determineMax

public static final double[] determineMax(double _c,
                                          Kernel kernel,
                                          ExampleSet exampleSet,
                                          int selectionType,
                                          int arraySize)

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.

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class Operator