Package org.encog.ml.factory

Source Code of org.encog.ml.factory.MLMethodFactory

/*
* Encog(tm) Core v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 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.ml.factory;

import org.encog.Encog;
import org.encog.EncogError;
import org.encog.ml.MLMethod;
import org.encog.plugin.EncogPluginBase;
import org.encog.plugin.EncogPluginService1;

/**
* This factory is used to create machine learning methods.
*/
public class MLMethodFactory {

  /**
   * String constant for feedforward neural networks.
   */
  public static final String TYPE_FEEDFORWARD = "feedforward";

  /**
   * String constant for RBF neural networks.
   */
  public static final String TYPE_RBFNETWORK = "rbfnetwork";

  /**
   * String constant for support vector machines.
   */
  public static final String TYPE_SVM = "svm";

  /**
   * String constant for SOMs.
   */
  public static final String TYPE_SOM = "som";

  /**
   * A probabilistic neural network. Supports both PNN & GRNN.
   */
  public static final String TYPE_PNN = "pnn";

  /**
   * Create a new machine learning method.
   *
   * @param methodType
   *            The method to create.
   * @param architecture
   *            The architecture string.
   * @param input
   *            The input count.
   * @param output
   *            The output count.
   * @return The newly created machine learning method.
   */
  public final MLMethod create(final String methodType,
      final String architecture, final int input, final int output) {
    for (EncogPluginBase plugin : Encog.getInstance().getPlugins()) {
      if (plugin instanceof EncogPluginService1) {
        MLMethod result = ((EncogPluginService1) plugin).createMethod(
            methodType, architecture, input, output);
        if (result != null) {
          return result;
        }
      }
    }

    throw new EncogError("Unknown method type: " + methodType);
  }

}
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