Package com.greentea.relaxation.algorithms

Examples of com.greentea.relaxation.algorithms.LearningAlgorithm

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   public static void main(String[] args) throws DataLoadException, LiveTerminatedException
   {
      CasCorAlgorithmFactory factory = new CasCorAlgorithmFactory();
      GAPopulation population = new GAPopulation();

      LearningAlgorithm winner = population.live(factory, 0.05, 16, 20, 1440000);

      serialize(winner.getNetwork());
   }
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         for (int i = 0; i < requiredEpochCount; ++i)
         {
            processEpoch(epochTime);
         }

         LearningAlgorithm winner = chromosomes.get(0).getLearningAlgorithm();
         for (Parameter p : ParametersUtils.resolveParameters(winner))
         {
            out(p.getName() + " = " + p.getValue());
         }
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      gaAlgorithmThread = new Thread(new Runnable()
      {
         public void run()
         {
            startGATime = new Date();
            LearningAlgorithm winner = null;
            try
            {
               population.setValuesRanges(owner.getValueRangesMap());
               winner = population
                       .live(algorithmFactory, mutationFactor, populationSize, epochesCount,
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      dataLoaderComboBox = new JComboBox(DataLoaderType.values());
   }

   private void analyze()
   {
      LearningAlgorithm learningAlgorithm = networkComponent.getLearningAlgorithm();
      if (learningAlgorithm.getLearningStatus() == ILearningController.LearningStatus.InProgress)
      {
         InfoDialog.showUserError(Localizer.getString(StringId.LEARNING_ON_NETWORK_NOT_FINISHED));
         return;
      }

      IForecastPerformer forecastPerformer = learningAlgorithm.getNetwork();
      if (!forecastPerformer.isReady())
      {
         InfoDialog.showUserError(Localizer.getString(StringId.NETWORK_NOT_LEARNED));
         return;
      }
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   public void recreateAlgorithm()
   {
      IAlgorithmFactory factory = componentOperations.getAlgorithmFactory(algorithmId);

      LearningAlgorithm previousLearningAlgorithm = getLearningAlgorithm();
      List<Parameter> parameters = ParametersUtils.resolveParameters(previousLearningAlgorithm);

      LearningAlgorithm newLearningAlgorithm = factory.createAlgorithm();
      ParametersUtils.apply(newLearningAlgorithm, parameters);

      setLearningAlgorithm(newLearningAlgorithm);
   }
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      final IAlgorithmFactory factory = componentOperations.getAlgorithmFactory(algorithmId);
      parametersOptimizationComponent.setAlgorithmFactory(new IAlgorithmFactory()
      {
         public LearningAlgorithm createAlgorithm()
         {
            LearningAlgorithm learningAlgorithm = factory.createAlgorithm();
            learningAlgorithm.setLearningData(learningData);
            learningAlgorithm.setTestData(testData);

            return learningAlgorithm;
         }
      });
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Related Classes of com.greentea.relaxation.algorithms.LearningAlgorithm

  • com.greentea.relaxation.algorithms.genetic.GAPopulation
  • com.greentea.relaxation.jnmf.gui.components.project.network.NetworkComponent
  • com.greentea.relaxation.jnmf.gui.components.project.network.optimization.GAParametersOptimizationComponent
  • com.greentea.relaxation.jnmf.gui.components.project.network.using.UsingNetworkComponent
  • com.greentea.relaxation.jnmf.model.Network
  • com.greentea.relaxation.jnmf.tests.GeneticTest
  • java.util.Date
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