/* * 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(); } } } }