Examples of process()


Examples of org.encog.workbench.dialogs.training.methods.InputBackpropagation.process()

  }

  private void performBPROP(ProjectEGFile file, MLDataSet trainingData) {
    InputBackpropagation dialog = new InputBackpropagation();
    if (dialog.process()) {
      double learningRate = dialog.getLearningRate().getValue();
      double momentum = dialog.getMomentum().getValue();
      int kFold = dialog.getKfold().getValue();
     
      if( kFold>0 ) {
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Examples of org.encog.workbench.dialogs.training.methods.InputGenetic.process()

  }

  private void performGenetic(ProjectEGFile file, MLDataSet trainingData) {
    InputGenetic dialog = new InputGenetic();
    if (dialog.process()) {
      final int populationSize = dialog.getPopulationSize().getValue();
      final double mutationPercent = dialog.getMutationPercent()
          .getValue();
      final double percentToMate = dialog.getPercentToMate().getValue();
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Examples of org.encog.workbench.dialogs.training.methods.InputInstar.process()

    sel.setVisible(true);

    if (sel.getSelected() == selectInstar) {
      InputInstar dialog = new InputInstar();

      if (dialog.process()) {
        double learnRate = dialog.getLearningRate().getValue();
        boolean init = dialog.getInitWeights().getValue();
        TrainInstar train = new TrainInstar((CPN)file.getObject(),trainingData,learnRate,init);
        startup(file,train, dialog.getMaxError().getValue()/100.0);
      }
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Examples of org.encog.workbench.dialogs.training.methods.InputLMA.process()

  }

  private void performLMA(ProjectEGFile file, MLDataSet trainingData) {
    InputLMA dialog = new InputLMA();

    if (dialog.process()) {
      LevenbergMarquardtTraining train = new LevenbergMarquardtTraining(
          (BasicNetwork) file.getObject(), trainingData);
      startup(file, train, dialog.getMaxError().getValue() / 100.0);
    }
  }
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Examples of org.encog.workbench.dialogs.training.methods.InputManhattan.process()

    }
  }

  private void performManhattan(ProjectEGFile file, MLDataSet trainingData) {
    InputManhattan dialog = new InputManhattan();
    if (dialog.process()) {
      double learningRate = dialog.getFixedDelta().getValue();
      int kFold = dialog.getKfold().getValue();

      if( kFold>0 ) {
        trainingData = this.wrapTrainingData(trainingData);
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Examples of org.encog.workbench.dialogs.training.methods.InputNEAT.process()

    }
  }

  private void performTrain() {
    InputNEAT dialog = new InputNEAT();
    if (dialog.process()) {
      ProjectEGFile popFile = dialog.getPopulation();
      NEATPopulation pop = (NEATPopulation) popFile.getObject();

      pop.setInputCount(2);
      pop.setOutputCount(1);
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Examples of org.encog.workbench.dialogs.training.methods.InputOutstar.process()

        startup(file,train, dialog.getMaxError().getValue()/100.0);
      }
    } else if (sel.getSelected() == selectOutstar) {
      InputOutstar dialog = new InputOutstar();

      if (dialog.process()) {
        double learnRate = dialog.getLearningRate().getValue();
        TrainOutstar train = new TrainOutstar((CPN)file.getObject(),trainingData,learnRate);
        startup(file,train, dialog.getMaxError().getValue()/100.0);
      }
    }
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Examples of org.encog.workbench.dialogs.training.methods.InputQPROP.process()

    }
  }
 
  private void performQPROP(ProjectEGFile file, MLDataSet trainingData) {
    InputQPROP dialog = new InputQPROP();
    if (dialog.process()) {
      double learningRate = dialog.getLearningRate().getValue();
     
      int kFold = dialog.getKfold().getValue();
     
      if( kFold>0 ) {
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Examples of org.encog.workbench.dialogs.training.methods.InputResilient.process()

    }
  }

  private void performRPROP(ProjectEGFile file, MLDataSet trainingData) {
    InputResilient dialog = new InputResilient();
    if (dialog.process()) {
      final double initialUpdate = dialog.getInitialUpdate().getValue();
      final double maxStep = dialog.getMaxStep().getValue();
           
      int kFold = dialog.getKfold().getValue();
     
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Examples of org.encog.workbench.dialogs.training.methods.InputSCG.process()

    }
  }

  private void performSCG(ProjectEGFile file, MLDataSet trainingData) {
    InputSCG dialog = new InputSCG();
    if (dialog.process()) {
      int kFold = dialog.getKfold().getValue();
     
      if( kFold>0 ) {
        trainingData = this.wrapTrainingData(trainingData);
      }
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