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source: stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/FeatureSelection/FeatureSelectionRegressionProblemData.cs @ 14389

Last change on this file since 14389 was 14186, checked in by swagner, 8 years ago

#2526: Updated year of copyrights in license headers

File size: 3.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2016 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 HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Parameters;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29using HeuristicLab.Problems.DataAnalysis;
30
31namespace HeuristicLab.Problems.Instances.DataAnalysis {
32  [StorableClass]
33  public class FeatureSelectionRegressionProblemData : RegressionProblemData {
34    private const string SelectedFeaturesParameterName = "SelectedFeatures";
35    private const string WeightsParameterName = "Weights";
36    private const string OptimalRSquaredParameterName = "R² (best solution)";
37
38    public IValueParameter<StringArray> SelectedFeaturesParameter {
39      get { return (IValueParameter<StringArray>)Parameters[SelectedFeaturesParameterName]; }
40    }
41
42    public IValueParameter<DoubleArray> WeightsParameter {
43      get { return (IValueParameter<DoubleArray>)Parameters[WeightsParameterName]; }
44    }
45
46    public IValueParameter<DoubleValue> OptimalRSquaredParameter {
47      get { return (IValueParameter<DoubleValue>)Parameters[OptimalRSquaredParameterName]; }
48    }
49
50    [StorableConstructor]
51    protected FeatureSelectionRegressionProblemData(bool deserializing)
52      : base(deserializing) {
53    }
54    protected FeatureSelectionRegressionProblemData(FeatureSelectionRegressionProblemData original, Cloner cloner)
55      : base(original, cloner) {
56    }
57
58    public FeatureSelectionRegressionProblemData(IDataset ds, IEnumerable<string> allowedInputVariables, string targetVariable, string[] selectedFeatures, double[] weights, double optimalRSquared)
59      : base(ds, allowedInputVariables, targetVariable) {
60      if (selectedFeatures.Length != weights.Length) throw new ArgumentException("Length of selected features vector does not match the length of the weights vector");
61      if (optimalRSquared < 0 || optimalRSquared > 1) throw new ArgumentException("Optimal R² is not in range [0..1]");
62      Parameters.Add(new FixedValueParameter<StringArray>(
63        SelectedFeaturesParameterName,
64        "Array of features used to generate the target values.",
65        new StringArray(selectedFeatures).AsReadOnly()));
66      Parameters.Add(new FixedValueParameter<DoubleArray>(
67        WeightsParameterName,
68        "Array of weights used to generate the target values.",
69        (DoubleArray)(new DoubleArray(weights).AsReadOnly())));
70      Parameters.Add(new FixedValueParameter<DoubleValue>(
71        OptimalRSquaredParameterName,
72        "R² of the optimal solution.",
73        (DoubleValue)(new DoubleValue(optimalRSquared).AsReadOnly())));
74    }
75
76    public override IDeepCloneable Clone(Cloner cloner) {
77      return new FeatureSelectionRegressionProblemData(this, cloner);
78    }
79  }
80}
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