Package com.github.neuralnetworks.training.rbm

Examples of com.github.neuralnetworks.training.rbm.DBNTrainer


    public static DNNLayerTrainer dnnLayerTrainer(DNN<?> dnn, Map<NeuralNetwork, OneStepTrainer<?>> layerTrainers, TrainingInputProvider trainingSet, TrainingInputProvider testingSet, OutputError error) {
  return new DNNLayerTrainer(layerTrainerProperties(dnn, layerTrainers, trainingSet, testingSet, error));
    }

    public static DBNTrainer dbnTrainer(DNN<?> dnn, Map<NeuralNetwork, OneStepTrainer<?>> layerTrainers, TrainingInputProvider trainingSet, TrainingInputProvider testingSet, OutputError error) {
  return new DBNTrainer(layerTrainerProperties(dnn, layerTrainers, trainingSet, testingSet, error));
    }
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  Map<NeuralNetwork, OneStepTrainer<?>> map = new HashMap<>();
  map.put(dbn.getFirstNeuralNetwork(), firstTrainer);
  map.put(dbn.getLastNeuralNetwork(), lastTrainer);

  // deep trainer
  DBNTrainer deepTrainer = TrainerFactory.dbnTrainer(dbn, map, trainInputProvider, null, null);

  Environment.getInstance().setExecutionMode(EXECUTION_MODE.SEQ);

  // layer pre-training
  deepTrainer.train();

  // fine tuning backpropagation
  BackPropagationTrainer<?> bpt = TrainerFactory.backPropagation(dbn, trainInputProvider, testInputProvider, new MultipleNeuronsOutputError(), new NNRandomInitializer(new MersenneTwisterRandomInitializer(-0.01f, 0.01f)), 0.01f, 0.5f, 0f, 0f);

  // log data
View Full Code Here

  Map<NeuralNetwork, OneStepTrainer<?>> map = new HashMap<>();
  map.put(dbn.getFirstNeuralNetwork(), firstTrainer);
  map.put(dbn.getLastNeuralNetwork(), lastTrainer);

  // deep trainer
  DBNTrainer deepTrainer = TrainerFactory.dbnTrainer(dbn, map, trainInputProvider, null, null);

  Environment.getInstance().setExecutionMode(EXECUTION_MODE.SEQ);

  // layer pre-training
  deepTrainer.train();

  // fine tuning backpropagation
  BackPropagationTrainer<?> bpt = TrainerFactory.backPropagation(dbn, trainInputProvider, testInputProvider, new MultipleNeuronsOutputError(), new NNRandomInitializer(new MersenneTwisterRandomInitializer(-0.01f, 0.01f)), 0.01f, 0.5f, 0f, 0f, 0f, 150, 150, 1000);

  // log data
View Full Code Here

    public static DNNLayerTrainer dnnLayerTrainer(DNN<?> dnn, Map<NeuralNetwork, OneStepTrainer<?>> layerTrainers, TrainingInputProvider trainingSet, TrainingInputProvider testingSet, OutputError error) {
  return new DNNLayerTrainer(layerTrainerProperties(dnn, layerTrainers, trainingSet, testingSet, error));
    }

    public static DBNTrainer dbnTrainer(DNN<?> dnn, Map<NeuralNetwork, OneStepTrainer<?>> layerTrainers, TrainingInputProvider trainingSet, TrainingInputProvider testingSet, OutputError error) {
  return new DBNTrainer(layerTrainerProperties(dnn, layerTrainers, trainingSet, testingSet, error));
    }
View Full Code Here

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