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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Clustering/ClusteringProblemData.cs @ 7823

Last change on this file since 7823 was 7823, checked in by sforsten, 12 years ago

#1784: merge branch ProblemInstancesRegressionAndClassification into trunk

File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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 HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.DataAnalysis {
28  [StorableClass]
29  [Item("ClusteringProblemData", "Represents an item containing all data defining a clustering problem.")]
30  public sealed class ClusteringProblemData : DataAnalysisProblemData, IClusteringProblemData, IStorableContent {
31    public string Filename { get; set; }
32
33    #region default data
34    private static double[,] kozaF1 = new double[,] {
35          {2.017885919, -1.449165046},
36          {1.30060506,  -1.344523885},
37          {1.147134798, -1.317989331},
38          {0.877182504, -1.266142284},
39          {0.852562452, -1.261020794},
40          {0.431095788, -1.158793317},
41          {0.112586002, -1.050908405},
42          {0.04594507,  -1.021989402},
43          {0.042572879, -1.020438113},
44          {-0.074027291,  -0.959859562},
45          {-0.109178553,  -0.938094706},
46          {-0.259721109,  -0.803635355},
47          {-0.272991057,  -0.387519561},
48          {-0.161978191,  -0.193611001},
49          {-0.102489983,  -0.114215349},
50          {-0.01469968, -0.014918985},
51          {-0.008863365,  -0.008942626},
52          {0.026751057, 0.026054094},
53          {0.166922436, 0.14309643},
54          {0.176953808, 0.1504144},
55          {0.190233418, 0.159916534},
56          {0.199800708, 0.166635331},
57          {0.261502822, 0.207600348},
58          {0.30182879,  0.232370249},
59          {0.83763905,  0.468046718}
60    };
61    private static Dataset defaultDataset;
62    private static IEnumerable<string> defaultAllowedInputVariables;
63
64    static ClusteringProblemData() {
65      defaultDataset = new Dataset(new string[] { "y", "x" }, kozaF1);
66      defaultDataset.Name = "Fourth-order Polynomial Function Benchmark Dataset";
67      defaultDataset.Description = "f(x) = x^4 + x^3 + x^2 + x^1";
68      defaultAllowedInputVariables = new List<string>() { "x", "y" };
69    }
70    #endregion
71
72    [StorableConstructor]
73    private ClusteringProblemData(bool deserializing) : base(deserializing) { }
74    [StorableHook(HookType.AfterDeserialization)]
75    private void AfterDeserialization() {
76    }
77
78
79    private ClusteringProblemData(ClusteringProblemData original, Cloner cloner)
80      : base(original, cloner) {
81    }
82    public override IDeepCloneable Clone(Cloner cloner) { return new ClusteringProblemData(this, cloner); }
83
84    public ClusteringProblemData()
85      : this(defaultDataset, defaultAllowedInputVariables) {
86    }
87
88    public ClusteringProblemData(Dataset dataset, IEnumerable<string> allowedInputVariables)
89      : base(dataset, allowedInputVariables) {
90    }
91  }
92}
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