#region License Information /* HeuristicLab * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab 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 General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections; using System.Collections.Generic; using System.Linq; using HeuristicLab.Data; namespace HeuristicLab.Problems.DataAnalysis.Benchmarks { public class HighGmcIL : RegressionRealWorldBenchmark { private const string fileName = "gmc_IL.csv"; public HighGmcIL() { Name = "McConaghy High gmc_IL"; Description = "Paper: Deterministic Symbolic Regression Technology, Genetic Programming Theory and Practice IX" + Environment.NewLine + "High-Dimensional Statistical Modeling and Analysis of Custom Integrated Circuits" + Environment.NewLine + "Authors: T. McConaghy" + Environment.NewLine + "Website: http://trent.st/ffx/"; } protected override List GetData() { csvFileParser = Benchmark.getParserForFile(fileName); targetVariable = csvFileParser.VariableNames.First(); inputVariables = new List(csvFileParser.VariableNames.Skip(1)); int trainingPartEnd = csvFileParser.Rows * 2 / 3; trainingPartition = new IntRange(0, trainingPartEnd); testPartition = new IntRange(trainingPartEnd, csvFileParser.Rows); return csvFileParser.Values; } } }