com.rapidminer.operator.meta
Class ESParameterOptimization

java.lang.Object
  com.rapidminer.tools.math.optimization.ec.es.ESOptimization
      com.rapidminer.operator.meta.ESParameterOptimization

All Implemented Interfaces:

Optimization

public class ESParameterOptimization
extends ESOptimization

Evolutionary Strategy approach for an evolutionary parameter optimization.

Author:

Ingo Mierswa

Field Summary

Fields inherited from class com.rapidminer.tools.math.optimization.ec.es.ESOptimization

BOLTZMANN_SELECTION, CUT_SELECTION, GAUSSIAN_MUTATION, INIT_TYPE_MAX, INIT_TYPE_MIN, INIT_TYPE_ONE, INIT_TYPE_RANDOM, INIT_TYPE_ZERO, MUTATION_TYPES, NO_MUTATION, NON_DOMINATED_SORTING_SELECTION, POPULATION_INIT_TYPES, RANK_SELECTION, ROULETTE_WHEEL, SELECTION_TYPES, SPARSITY_MUTATION, STOCHASTIC_UNIVERSAL, SWITCHING_MUTATION, TOURNAMENT_SELECTION, UNIFORM_SELECTION

Constructor Summary

ESParameterOptimization(EvolutionaryParameterOptimizationOperator operator, int individualSize, int initType, int maxIterations, int generationsWithoutImprovement, int popSize, int selectionType, double tournamentFraction, boolean keepBest, int mutationType, double crossoverProb, boolean showPlot, RandomGenerator random, LoggingHandler logging)
Creates a new evolutionary SVM optimization.

Method Summary

PerformanceVector	evaluateIndividual(Individual individual) Subclasses must implement this method to calculate the fitness of the given individual.
void	nextIteration() This method is invoked after each evaluation.

Methods inherited from class com.rapidminer.tools.math.optimization.ec.es.ESOptimization

evaluate, getBestFitnessEver, getBestFitnessInGeneration, getBestPerformanceEver, getBestValuesEver, getGeneration, getMax, getMin, getPopulation, getValueType, increaseCurrentEvaluationCounter, increaseTotalEvaluationCounter, optimize, setMax, setMin, setValueType

Methods inherited from class java.lang.Object

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

Constructor Detail

ESParameterOptimization

public ESParameterOptimization(EvolutionaryParameterOptimizationOperator operator,
                               int individualSize,
                               int initType,
                               int maxIterations,
                               int generationsWithoutImprovement,
                               int popSize,
                               int selectionType,
                               double tournamentFraction,
                               boolean keepBest,
                               int mutationType,
                               double crossoverProb,
                               boolean showPlot,
                               RandomGenerator random,
                               LoggingHandler logging)

Creates a new evolutionary SVM optimization.

Method Detail

evaluateIndividual

public PerformanceVector evaluateIndividual(Individual individual)
                                     throws OperatorException

Description copied from class: ESOptimization

Subclasses must implement this method to calculate the fitness of the given individual. Please note that null might be returned for non-valid individuals. The fitness will be maximized.

Specified by:

evaluateIndividual in class ESOptimization

Throws:

OperatorException

nextIteration

public void nextIteration()
                   throws OperatorException

Description copied from class: ESOptimization

This method is invoked after each evaluation. The default implementation does nothing but subclasses might implement this method to support online plotting or logging.

Overrides:

nextIteration in class ESOptimization

Throws:

OperatorException