Package org.encog.neural.pnn

Examples of org.encog.neural.pnn.PNNOutputMode

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  public final TempDir TEMP_DIR = new TempDir();
  public final File EG_FILENAME = TEMP_DIR.createFile("encogtest.eg");
  public final File SERIAL_FILENAME = TEMP_DIR.createFile("encogtest.ser");
   
  public BasicPNN create() {
    PNNOutputMode mode = PNNOutputMode.Regression;

    BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 1);

    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,
        XOR.XOR_IDEAL);
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  @Test
  public void testRegPNN() throws Throwable
  {
   
    PNNOutputMode mode = PNNOutputMode.Regression;
    BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 1);

    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,
        XOR.XOR_IDEAL);
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  @Test
  public void testClassifyPNN() throws Throwable
  {
   
    PNNOutputMode mode = PNNOutputMode.Classification;
    BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 2);

    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,
        XOR.XOR_IDEAL);
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    final int inputCount = inputLayer.getCount();
    final int outputCount = outputLayer.getCount();

    PNNKernelType kernel;
    PNNOutputMode outmodel;

    if (pnnLayer.getName().equalsIgnoreCase("c")) {
      outmodel = PNNOutputMode.Classification;
    } else if (pnnLayer.getName().equalsIgnoreCase("r")) {
      outmodel = PNNOutputMode.Regression;
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    final int inputCount = inputLayer.getCount();
    final int outputCount = outputLayer.getCount();

    PNNKernelType kernel;
    PNNOutputMode outmodel;

    if (pnnLayer.getName().equalsIgnoreCase("c")) {
      outmodel = PNNOutputMode.Classification;
    } else if (pnnLayer.getName().equalsIgnoreCase("r")) {
      outmodel = PNNOutputMode.Regression;
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  public final TempDir TEMP_DIR = new TempDir();
  public final File EG_FILENAME = TEMP_DIR.createFile("encogtest.eg");
  public final File SERIAL_FILENAME = TEMP_DIR.createFile("encogtest.ser");
   
  public BasicPNN create() {
    PNNOutputMode mode = PNNOutputMode.Regression;

    BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 1);

    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,
        XOR.XOR_IDEAL);
View Full Code Here
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  @Test
  public void testRegPNN() throws Throwable
  {
   
    PNNOutputMode mode = PNNOutputMode.Regression;
    BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 1);

    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,
        XOR.XOR_IDEAL);
View Full Code Here
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  @Test
  public void testClassifyPNN() throws Throwable
  {
   
    PNNOutputMode mode = PNNOutputMode.Classification;
    BasicPNN network = new BasicPNN(PNNKernelType.Gaussian, mode, 2, 2);

    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR.XOR_INPUT,
        XOR.XOR_IDEAL);
View Full Code Here
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Related Classes of org.encog.neural.pnn.PNNOutputMode

  • org.encog.ml.factory.method.PNNFactory
  • org.encog.neural.networks.training.TestTraining
  • org.encog.persist.TestPersistPNN
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