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A

AbstractHypothesis<T extends AbstractHypothesis> - Class in de.sfuhrm.genetic

Hypothesis base class.

AbstractHypothesis() - Constructor for class de.sfuhrm.genetic.AbstractHypothesis

C

calculateFitness() - Method in class de.sfuhrm.genetic.AbstractHypothesis

Calculates the fitness of this hypothesis.

crossover(List<H>, Collection<H>) - Method in class de.sfuhrm.genetic.GeneticAlgorithm

Cross-overs a fraction of crossOverRate hypothesis relative to their fitness.

crossOver(T) - Method in class de.sfuhrm.genetic.AbstractHypothesis

Returns a two-element crossover offspring of this and the other hypothesis.

D

de.sfuhrm.genetic - package de.sfuhrm.genetic

Base classes for a genetic algorithm.

F

findMaximum(Function<H, Boolean>, Supplier<H>) - Method in class de.sfuhrm.genetic.GeneticAlgorithm

Perform the genetic operation.

G

GeneticAlgorithm<H extends AbstractHypothesis<H>> - Class in de.sfuhrm.genetic

Generic genetic algorithm implementation.

GeneticAlgorithm(double, double, int) - Constructor for class de.sfuhrm.genetic.GeneticAlgorithm

Constructs a new genetic algorithm.

M

max(Collection<H>) - Method in class de.sfuhrm.genetic.GeneticAlgorithm

Find the maximum fitness element of the given collection.

mutate() - Method in class de.sfuhrm.genetic.AbstractHypothesis

Implements the mutation operator.

mutate(List<H>) - Method in class de.sfuhrm.genetic.GeneticAlgorithm

Mutates a fraction of mutationRate hypothesis.

P

probabilisticSelect(List<H>, Collection<H>, boolean) - Method in class de.sfuhrm.genetic.GeneticAlgorithm

Probabilistically selects one hypothesis relative to the selection probability of it.

R

randomInit() - Method in class de.sfuhrm.genetic.AbstractHypothesis

Randomly initialize the hypothesis.

S

select(List<H>, Collection<H>) - Method in class de.sfuhrm.genetic.GeneticAlgorithm

Selects a fraction of 1-crossOverRate hypothesis relative to their fitness.

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