Examples of RbfNetwork

Examples of org.encog.neural.rbf.RBFNetwork

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      t = RBFEnum.MexicanHat;
    } else {
      t = RBFEnum.Gaussian;
    }

    final RBFNetwork result = new RBFNetwork(inputCount,
        rbfLayer.getCount(), outputCount, t);

    return result;
  }
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Examples of org.encog.neural.rbf.RBFNetwork

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    final ParamsHolder holder = new ParamsHolder(rbfLayer.getParams());

    final int rbfCount = holder.getInt("C", true, 0);

    final RBFNetwork result = new RBFNetwork(inputCount, rbfCount,
        outputCount, t);

    return result;
  }
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Examples of org.encog.neural.rbf.RBFNetwork

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  public final File SERIAL_FILENAME = TEMP_DIR.createFile("encogtest.ser");
 
  public void testPersistNetworkRBF()
  {
    MLDataSet trainingSet = XOR.createXORDataSet();
    RBFNetwork network = new RBFNetwork(2,4,1, RBFEnum.Gaussian);

    SVDTraining training = new SVDTraining(network,trainingSet);
    training.iteration();
    XOR.verifyXOR(network, 0.1);
   
    EncogDirectoryPersistence.saveObject(EG_FILENAME, network);
    RBFNetwork network2 = (RBFNetwork)EncogDirectoryPersistence.loadObject(EG_FILENAME);

    XOR.verifyXOR(network2, 0.1);   
  }
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Examples of org.encog.neural.rbf.RBFNetwork

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  }
 
  public void testFactoryRBF() {
    String architecture = "?->GAUSSIAN(c=4)->?";
    MLMethodFactory factory = new MLMethodFactory();
    RBFNetwork network = (RBFNetwork)factory.create(MLMethodFactory.TYPE_RBFNETWORK, architecture, 1, 4);
    Assert.assertEquals(1,network.getInputCount());
    Assert.assertEquals(4,network.getOutputCount());
    Assert.assertEquals(4,network.getRBF().length); 
  }
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Examples of org.encog.neural.rbf.RBFNetwork

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   *
   * @return The neural network.
   */
  public MLMethod generate() {

    RBFNetwork result = new RBFNetwork(inputNeurons, this.hiddenNeurons ,outputNeurons,this.rbfType);
    return result;
  }
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Examples of org.neuroph.nnet.RbfNetwork

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   * @param outputNeuronsCount number of neurons in output layer
   * @return instance of RBF network
   */
  public static RbfNetwork createRbfNetwork(int inputNeuronsCount,
      int rbfNeuronsCount, int outputNeuronsCount) {
    RbfNetwork nnet = new RbfNetwork(inputNeuronsCount, rbfNeuronsCount,
        outputNeuronsCount);
    return nnet;
  }
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