Package org.encog.neural.pattern

Source Code of org.encog.neural.pattern.ADALINEPattern

/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*  
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.neural.pattern;

import org.encog.engine.network.activation.ActivationFunction;
import org.encog.engine.network.activation.ActivationLinear;
import org.encog.mathutil.randomize.RangeRandomizer;
import org.encog.ml.MLMethod;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.layers.BasicLayer;
import org.encog.neural.networks.layers.Layer;

/**
* Construct an ADALINE neural network.
*/
public class ADALINEPattern implements NeuralNetworkPattern {

  /**
   * The number of neurons in the input layer.
   */
  private int inputNeurons;

  /**
   * The number of neurons in the output layer.
   */
  private int outputNeurons;


  /**
   * Not used, the ADALINE has no hidden layers, this will throw an error.
   *
   * @param count
   *            The neuron count.
   */
  public void addHiddenLayer(final int count) {
    throw new PatternError("An ADALINE network has no hidden layers.");
  }

  /**
   * Clear out any parameters.
   */
  public void clear() {
    this.inputNeurons = 0;
    this.outputNeurons = 0;
  }

  /**
   * Generate the network.
   *
   * @return The generated network.
   */
  public MLMethod generate() {
    final BasicNetwork network = new BasicNetwork();

    final Layer inputLayer = new BasicLayer(new ActivationLinear(), true,
        this.inputNeurons);
    final Layer outputLayer = new BasicLayer(new ActivationLinear(), false,
        this.outputNeurons);

    network.addLayer(inputLayer);
    network.addLayer(outputLayer);
    network.getStructure().finalizeStructure();

    (new RangeRandomizer(-0.5, 0.5)).randomize(network);

    return network;
  }

  /**
   * Not used, ADALINE does not use custom activation functions.
   *
   * @param activation
   *            Not used.
   */
  public void setActivationFunction(final ActivationFunction activation) {
    throw new PatternError( "A ADALINE network can't specify a custom activation function.");
  }

  /**
   * Set the input neurons.
   *
   * @param count
   *            The number of neurons in the input layer.
   */
  public void setInputNeurons(final int count) {
    this.inputNeurons = count;
  }

  /**
   * Set the output neurons.
   *
   * @param count
   *            The number of neurons in the output layer.
   */
  public void setOutputNeurons(final int count) {
    this.outputNeurons = count;
  }

}
TOP

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

TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.