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source: trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/FeatureSelection/FeatureSelectionRegressionProblemData.cs @ 9650

Last change on this file since 9650 was 9456, checked in by swagner, 12 years ago

Updated copyright year and added some missing license headers (#1889)

File size: 3.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Problems.DataAnalysis;
31using HeuristicLab.Random;
32
33namespace HeuristicLab.Problems.Instances.DataAnalysis {
34  public class FeatureSelectionRegressionProblemData : RegressionProblemData {
35    private const string SelectedFeaturesParameterName = "SelectedFeatures";
36    private const string WeightsParameterName = "Weights";
37    private const string OptimalRSquaredParameterName = "R² (best solution)";
38
39    public IValueParameter<StringArray> SelectedFeaturesParameter {
40      get { return (IValueParameter<StringArray>)Parameters[SelectedFeaturesParameterName]; }
41    }
42
43    public IValueParameter<DoubleArray> WeightsParameter {
44      get { return (IValueParameter<DoubleArray>)Parameters[WeightsParameterName]; }
45    }
46
47    public IValueParameter<DoubleValue> OptimalRSquaredParameter {
48      get { return (IValueParameter<DoubleValue>)Parameters[OptimalRSquaredParameterName]; }
49    }
50
51    [StorableConstructor]
52    protected FeatureSelectionRegressionProblemData(bool deserializing)
53      : base(deserializing) {
54    }
55    protected FeatureSelectionRegressionProblemData(FeatureSelectionRegressionProblemData original, Cloner cloner)
56      : base(original, cloner) {
57    }
58
59    public FeatureSelectionRegressionProblemData(Dataset ds, IEnumerable<string> allowedInputVariables, string targetVariable, string[] selectedFeatures, double[] weights, double optimalRSquared)
60      : base(ds, allowedInputVariables, targetVariable) {
61      if (selectedFeatures.Length != weights.Length) throw new ArgumentException("Length of selected features vector does not match the length of the weights vector");
62      if (optimalRSquared < 0 || optimalRSquared > 1) throw new ArgumentException("Optimal R² is not in range [0..1]");
63      Parameters.Add(new FixedValueParameter<StringArray>(
64        SelectedFeaturesParameterName,
65        "Array of features used to generate the target values.",
66        new StringArray(selectedFeatures).AsReadOnly()));
67      Parameters.Add(new FixedValueParameter<DoubleArray>(
68        WeightsParameterName,
69        "Array of weights used to generate the target values.",
70        (DoubleArray)(new DoubleArray(weights).AsReadOnly())));
71      Parameters.Add(new FixedValueParameter<DoubleValue>(
72        OptimalRSquaredParameterName,
73        "R² of the optimal solution.",
74        (DoubleValue)(new DoubleValue(optimalRSquared).AsReadOnly())));
75    }
76
77    public override IDeepCloneable Clone(Cloner cloner) {
78      return new FeatureSelectionRegressionProblemData(this, cloner);
79    }
80  }
81}
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