Package org.encog.ml.factory.train

Source Code of org.encog.ml.factory.train.QuickPropFactory

/*
* 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.ml.factory.train;

import java.util.Map;

import org.encog.ml.MLMethod;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.factory.MLTrainFactory;
import org.encog.ml.factory.parse.ArchitectureParse;
import org.encog.ml.train.MLTrain;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.training.propagation.quick.QuickPropagation;
import org.encog.util.ParamsHolder;

/**
* A factory for quick propagation training.
*
*/
public class QuickPropFactory {

  /**
   * Create a quick propagation trainer.
   *
   * @param method
   *            The method to use.
   * @param training
   *            The training data to use.
   * @param argsStr
   *            The arguments to use.
   * @return The newly created trainer.
   */
  public MLTrain create(final MLMethod method,
      final MLDataSet training, final String argsStr) {

    final Map<String, String> args = ArchitectureParse.parseParams(argsStr);
    final ParamsHolder holder = new ParamsHolder(args);

    final double learningRate = holder.getDouble(
        MLTrainFactory.PROPERTY_LEARNING_RATE, false, 2.0);
   
    return new QuickPropagation((BasicNetwork) method, training, learningRate);
  }
}
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