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

java.lang.Object
  com.rapidminer.tools.math.optimization.ec.es.ESOptimization
      com.rapidminer.operator.learner.functions.kernel.KernelLogisticRegressionOptimization

All Implemented Interfaces:

Optimization

public class KernelLogisticRegressionOptimization
extends ESOptimization

Evolutionary Strategy approach for optimization of the logistic regression problem.

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

KernelLogisticRegressionOptimization(ExampleSet exampleSet, Kernel kernel, double c, int initType, int maxIterations, int generationsWithoutImprovement, int popSize, int selectionType, double tournamentFraction, boolean keepBest, int mutationType, double crossoverProb, boolean showConvergencePlot, 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.
Model	train()

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

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

Methods inherited from class java.lang.Object

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

Constructor Detail

KernelLogisticRegressionOptimization

public KernelLogisticRegressionOptimization(ExampleSet exampleSet,
                                            Kernel kernel,
                                            double c,
                                            int initType,
                                            int maxIterations,
                                            int generationsWithoutImprovement,
                                            int popSize,
                                            int selectionType,
                                            double tournamentFraction,
                                            boolean keepBest,
                                            int mutationType,
                                            double crossoverProb,
                                            boolean showConvergencePlot,
                                            RandomGenerator random,
                                            LoggingHandler logging)

Creates a new evolutionary SVM optimization.

Method Detail

evaluateIndividual

public PerformanceVector evaluateIndividual(Individual individual)

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

train

public Model train()
            throws OperatorException

Throws:

OperatorException