Examples of BestMatchingUnit

org.encog.neural.som.training.basic.BestMatchingUnit
The "Best Matching Unit" or BMU is a very important concept in the training for a SOM. The BMU is the output neuron that has weight connections to the input neurons that most closely match the current input vector. This neuron (and its "neighborhood") are the neurons that will receive training. This class also tracks the worst distance (of all BMU's). This gives some indication of how well the network is trained, and thus becomes the "error" of the entire network. @author jeff

Examples of org.encog.neural.som.training.basic.BestMatchingUnit

   * {@inheritDoc}
   */
  @Override
  public final double calculateError(final MLDataSet data) {


    final BestMatchingUnit bmu = new BestMatchingUnit(this);


    bmu.reset();


    // Determine the BMU for each training element.
    for (final MLDataPair pair : data) {
      final MLData input = pair.getInput();
      bmu.calculateBMU(input);
    }


    // update the error
    return bmu.getWorstDistance() / 100.0;
  }

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Examples of org.encog.neural.som.training.basic.BestMatchingUnit

   * {@inheritDoc}
   */
  @Override
  public double calculateError(final MLDataSet data) {


    final BestMatchingUnit bmu = new BestMatchingUnit(this);


    bmu.reset();


    // Determine the BMU for each training element.
    for (final MLDataPair pair : data) {
      final MLData input = pair.getInput();
      bmu.calculateBMU(input);
    }


    // update the error
    return bmu.getWorstDistance() / 100.0;
  }

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