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source: branches/RegressionBenchmarks/HeuristicLab.Problems.DataAnalysis.Benchmarks/3.4/RegressionGenerator/RegressionToyBenchmark.cs @ 7127

Last change on this file since 7127 was 7127, checked in by sforsten, 12 years ago

#1669:
-Spatial co-evolution benchmark has been added
-Benchmarks of Trent McConaghy have been added
-2 Classification benchmarks have been added (Mammography and Iris dataset)
-Training and test set include now all samples from the dataset
-Load button and combo box are now disabled when the algorithm is running

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.Generic;
23using System.Linq;
24using HeuristicLab.Common;
25
26namespace HeuristicLab.Problems.DataAnalysis.Benchmarks {
27  public abstract class RegressionToyBenchmark : RegressionBenchmark {
28
29    protected RegressionToyBenchmark() { }
30    protected RegressionToyBenchmark(RegressionToyBenchmark original, Cloner cloner)
31      : base(original, cloner) {
32    }
33
34    protected abstract List<List<double>> GenerateInput();
35
36    protected abstract List<double> GenerateTarget(List<List<double>> data);
37
38    public override IDataAnalysisProblemData GenerateProblemData() {
39      List<string> varNames = new List<string>();
40      varNames.Add(this.TargetVariable);
41      varNames.AddRange(this.InputVariable);
42
43      List<List<double>> dataList = GenerateInput();
44
45      dataList.Insert(0, GenerateTarget(dataList));
46
47      Dataset dataset = new Dataset(varNames, dataList);
48
49      RegressionProblemData problemData = new RegressionProblemData(dataset, dataset.DoubleVariables.Skip(1), dataset.DoubleVariables.First());
50
51      problemData.Name = "Data generated for benchmark problem \"" + this.Name + "\"";
52      problemData.Description = this.Description;
53
54      problemData.TestPartition.Start = this.TestPartition.Start;
55      problemData.TestPartition.End = this.TestPartition.End;
56
57      problemData.TrainingPartition.Start = this.TrainingPartition.Start;
58      problemData.TrainingPartition.End = this.TrainingPartition.End;
59
60      return problemData;
61    }
62  }
63}
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