Package org.neuroph.nnet.learning

Examples of org.neuroph.nnet.learning.MomentumBackpropagation

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    // set input and output cells for network
                  NeuralNetworkFactory.setDefaultIO(this);

                  // set learnng rule
    //this.setLearningRule(new BackPropagation(this));
    this.setLearningRule(new MomentumBackpropagation());
               // this.setLearningRule(new DynamicBackPropagation());
   
    // flatten the network, if desired
    if( Neuroph.getInstance().shouldFlattenNetworks() ) {
      FlatNetworkPlugin.flattenNeuralNetworkNetwork(this);
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                // set learning rule
                if (learningRule.getName().equals(BackPropagation.class.getName()))  {
                    nnet.setLearningRule(new BackPropagation());
                } else if (learningRule.getName().equals(MomentumBackpropagation.class.getName())) {
                    nnet.setLearningRule(new MomentumBackpropagation());
                } else if (learningRule.getName().equals(DynamicBackPropagation.class.getName())) {
                    nnet.setLearningRule(new DynamicBackPropagation());
                }

                // connect io
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    neuralNetwork.setLabel(label);
    PluginBase imageRecognitionPlugin = new ImageRecognitionPlugin(samplingResolution, colorMode);
    neuralNetwork.addPlugin(imageRecognitionPlugin);

    assignLabelsToOutputNeurons(neuralNetwork, imageLabels);
                neuralNetwork.setLearningRule(new MomentumBackpropagation());

            return neuralNetwork;
  }
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Related Classes of org.neuroph.nnet.learning.MomentumBackpropagation

  • org.neuroph.contrib.imgrec.ImageRecognitionHelper
  • org.neuroph.core.Weight
  • org.neuroph.nnet.MultiLayerPerceptron
  • org.neuroph.util.NeuralNetworkFactory
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