/*
* Encog(tm) Examples v2.4
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
*
* Copyright 2008-2010 by Heaton Research Inc.
*
* Released under the LGPL.
*
* This is free software; you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2.1 of
* the License, or (at your option) any later version.
*
* This software is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this software; if not, write to the Free
* Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
* 02110-1301 USA, or see the FSF site: http://www.fsf.org.
*
* Encog and Heaton Research are Trademarks of Heaton Research, Inc.
* For information on Heaton Research trademarks, visit:
*
* http://www.heatonresearch.com/copyright.html
*/
package org.encog.examples.neural.predict.market;
import org.encog.util.logging.Logging;
/**
* Use the saved market neural network, and now attempt to predict for today, and the
* last 60 days and see what the results are.
*/
public class MarketPredict {
public static void main(String[] args)
{
Logging.stopConsoleLogging();
if( args.length<1 ) {
System.out.println("Specify one of the following arguments: generate, train, incremental, selective or evaluate.");
}
else
{
if( args[0].equalsIgnoreCase("generate") ) {
MarketBuildTraining.generate();
}
else if( args[0].equalsIgnoreCase("train") ) {
MarketTrain.train();
}
else if( args[0].equalsIgnoreCase("evaluate") ) {
MarketEvaluate.evaluate();
} else if( args[0].equalsIgnoreCase("prune") ) {
MarketPrune.incremental();
}
}
}
}