Examples of org.encog.neural.pattern.RadialBasisPattern

        //We have added the ability to include wider neurons on the sample space boundary which greatly
        //improves fitting to flats
        boolean includeEdgeRBFs = true;


        //General setup is the same as before
        RadialBasisPattern pattern = new RadialBasisPattern();
        pattern.setInputNeurons(dimensions);
        pattern.setOutputNeurons(1);


        //Total number of neurons required.
        //Total number of Edges is calculated possibly for future use but not used any further here
        int numNeurons = (int)Math.pow(numNeuronsPerDimension, dimensions);
        int numEdges = (int)(dimensions * Math.pow(2, dimensions - 1));


        pattern.addHiddenLayer(numNeurons);


        RBFNetwork network = (RBFNetwork)pattern.generate();


        //Position the multidimensional RBF neurons, with equal spacing, within the provided sample space from 0 to 1.
        network.setRBFCentersAndWidthsEqualSpacing(0, 1, RBFEnum.Gaussian, volumeNeuronWidth, includeEdgeRBFs);


        //Create some training data that can not easily be represented by gaussians

  private static MLMethod createRBF() {
    CreateRBFDialog dialog = new CreateRBFDialog(EncogWorkBench
        .getInstance().getMainWindow());
    if (dialog.process()) {
      RBFEnum type = dialog.getRBFType();
      RadialBasisPattern rbf = new RadialBasisPattern();
      rbf.setInputNeurons(dialog.getInputCount().getValue());
      rbf.addHiddenLayer(dialog.getHiddenCount().getValue());
      rbf.setOutputNeurons(dialog.getOutputCount().getValue());
      rbf.setRBF(type);
      return rbf.generate();
    } else
      return null;


  }

Examples of org.encog.neural.pattern.RadialBasisPattern

Related Classes of org.encog.neural.pattern.RadialBasisPattern