Uses of Class
net.bmahe.genetics4j.core.spec.EvolutionResult
Packages that use EvolutionResult
Package
Description
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Uses of EvolutionResult in net.bmahe.genetics4j.core
Methods in net.bmahe.genetics4j.core that return EvolutionResultModifier and TypeMethodDescriptionEASystem.evolve()Executes the complete evolutionary algorithm process until termination criteria are met. -
Uses of EvolutionResult in net.bmahe.genetics4j.core.spec
Subclasses of EvolutionResult in net.bmahe.genetics4j.core.specModifier and TypeClassDescriptionfinal classImmutableEvolutionResult<T extends Comparable<T>>Immutable implementation ofEvolutionResult.Methods in net.bmahe.genetics4j.core.spec that return EvolutionResultModifier and TypeMethodDescriptionImmutableEvolutionResult.Builder.build()Builds a newEvolutionResult.static <T extends Comparable<T>>
EvolutionResult<T> ImmutableEvolutionResult.copyOf(EvolutionResult<T> instance) Creates an immutable copy of aEvolutionResultvalue.static <T extends Comparable<T>>
EvolutionResult<T> ImmutableEvolutionResult.of(AbstractEAConfiguration<T> eaConfiguration, long generation, Iterable<? extends Genotype> population, Iterable<? extends T> fitness) Construct a new immutableEvolutionResultinstance.static <T extends Comparable<T>>
EvolutionResult<T> ImmutableEvolutionResult.of(AbstractEAConfiguration<T> eaConfiguration, long generation, List<Genotype> population, List<T> fitness) Construct a new immutableEvolutionResultinstance.Methods in net.bmahe.genetics4j.core.spec with parameters of type EvolutionResultModifier and TypeMethodDescriptionstatic <T extends Comparable<T>>
EvolutionResult<T> ImmutableEvolutionResult.copyOf(EvolutionResult<T> instance) Creates an immutable copy of aEvolutionResultvalue.ImmutableEvolutionResult.Builder.from(EvolutionResult<T> instance) Fill a builder with attribute values from the providedEvolutionResultinstance. -
Uses of EvolutionResult in net.bmahe.genetics4j.samples.mixturemodel
Methods in net.bmahe.genetics4j.samples.mixturemodel that return EvolutionResultModifier and TypeMethodDescriptionMooCPU.run(int maxPossibleDistributions, double[][] samples, float[] x, float[] y, String algorithmName, Collection<Genotype> seedPopulation) SingleObjectiveMethod.run(int maxPossibleDistributions, double[][] samples, float[] x, float[] y, String algorithmName, Collection<Genotype> seedPopulation) Methods in net.bmahe.genetics4j.samples.mixturemodel with parameters of type EvolutionResultModifier and TypeMethodDescriptionstatic voidClusteringUtils.categorizeByNumClusters(int distributionNumParameters, int maxPossibleDistributions, float[] x, float[] y, double[][] samplesDouble, EvolutionResult<FitnessVector<Float>> evolutionResult, String baseDir, String type) static Map<Integer, Individual<FitnessVector<Float>>> ClusteringUtils.groupByNumClusters(double[][] samplesDouble, EvolutionResult<FitnessVector<Float>> evolutionResult) voidMooGPU.run(int maxPossibleDistributions, int numDistributions, double[][] samplesDouble, float[][] samples, float[] x, float[] y, String algorithmName, Collection<Genotype> seedPopulation, EvolutionResult<FitnessVector<Float>> bestCPUResult)