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source: branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/ClassificationGenerator/ClassificationRealWorldBenchmark.cs @ 7317

Last change on this file since 7317 was 7138, checked in by sforsten, 13 years ago

#1669:
-Iris benchmark has been corrected and data set will ordered randomly
-Benchmarks of Trent McConaghy have been corrected
-Descriptions have been added (Mammography and Iris)
-Bug fix in ClassificationRealWorldBenchmark

File size: 2.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System.Collections;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26
27namespace HeuristicLab.Problems.DataAnalysis.Benchmarks {
28  public abstract class ClassificationRealWorldBenchmark : ClassificationBenchmark {
29
30    protected TableFileParser csvFileParser;
31
32    protected ClassificationRealWorldBenchmark() { }
33    protected ClassificationRealWorldBenchmark(ClassificationRealWorldBenchmark original, Cloner cloner)
34      : base(original, cloner) {
35    }
36
37    protected abstract List<IList> GetData();
38
39    public override IDataAnalysisProblemData GenerateProblemData() {
40      List<IList> dataList = GetData();
41
42      List<string> varNames = new List<string>();
43      varNames.Add(this.TargetVariable);
44      varNames.AddRange(InputVariable);
45
46      Dataset dataset = new Dataset(varNames, dataList);
47
48      ClassificationProblemData problemData = new ClassificationProblemData(dataset, dataset.DoubleVariables.Skip(1), dataset.DoubleVariables.First());
49
50      problemData.Name = "Data generated for benchmark problem \"" + this.Name + "\"";
51      problemData.Description = this.Description;
52
53      problemData.TestPartition.Start = this.TestPartition.Start;
54      problemData.TestPartition.End = this.TestPartition.End;
55
56      problemData.TrainingPartition.Start = this.TrainingPartition.Start;
57      problemData.TrainingPartition.End = this.TrainingPartition.End;
58
59      return problemData;
60    }
61  }
62}
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