Package org.encog.ml.genetic.crossover

Examples of org.encog.ml.genetic.crossover.Splice

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    final Population population = new BasicPopulation(populationSize);
    getGenetic().setMutationPercent(mutationPercent);
    getGenetic().setMatingPopulation(percentToMate * 2);
    getGenetic().setPercentToMate(percentToMate);
    getGenetic().setCrossover(
        new Splice(network.getStructure().calculateSize() / 3));
    getGenetic().setMutate(new MutatePerturb(4.0));
    getGenetic().setPopulation(population);
    for (int i = 0; i < population.getPopulationSize(); i++) {
      final BasicNetwork chromosomeNetwork = (BasicNetwork) network
          .clone();
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    GeneticAlgorithm genetic = new BasicGeneticAlgorithm();
    initPopulation(genetic);
    genetic.setMutationPercent(MUTATION_PERCENT);
    genetic.setPercentToMate(PERCENT_TO_MATE);
    genetic.setMatingPopulation(MATING_POPULATION_PERCENT);
    genetic.setCrossover(new Splice(CUT_LENGTH));
    genetic.setMutate(new MutateShuffle());
   
    boolean done = false;
    int iteration = 0;
   
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    // create the operators
    final int s = Math
        .max(defaultSpecies.getMembers().get(0).size() / 5, 1);
    getGenetic().setPopulation(population);

    this.genetic.addOperation(0.9, new Splice(s));
    this.genetic.addOperation(0.1, new MutatePerturb(1.0));
  }
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Related Classes of org.encog.ml.genetic.crossover.Splice

  • org.encog.examples.nonlinear.basicstrategy.Play21
  • org.encog.ml.genetic.genome.ArrayGenome
  • org.encog.ml.genetic.MLMethodGeneticAlgorithm
  • org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm
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