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source: branches/LearningClassifierSystems/HeuristicLab.Problems.VariableVectorClassification/3.3/VariableVectorClassificationProblemData.cs @ 14778

Last change on this file since 14778 was 9494, checked in by sforsten, 12 years ago

#1980:

  • renamed algorithm Learning Classifier System to XCS
  • DecisionListSolution and XCSSolution show more information
  • VariableVectorClassificationProblemData can now also import datasets where the last variable is not the target variable
File size: 7.0 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;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.ConditionActionEncoding;
29using HeuristicLab.Encodings.VariableVector;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32using HeuristicLab.Problems.ConditionActionClassification;
33using HeuristicLab.Problems.DataAnalysis;
34
35namespace HeuristicLab.Problems.VariableVectorClassification {
36  [StorableClass]
37  [Item("CombinedIntegerVectorClassificationProblemData", "A problem data for LCS.")]
38  public class VariableVectorClassificationProblemData : ConditionActionClassificationProblemData, IVariableVectorClassificationProblemData {
39
40    #region parameter properites
41    public IValueParameter<VariableVector> SampleVariableVectorParameter {
42      get { return (IValueParameter<VariableVector>)Parameters["SampleVariableVector"]; }
43    }
44    public IFixedValueParameter<PercentValue> SpreadPercentageParameter {
45      get { return (IFixedValueParameter<PercentValue>)Parameters["SpreadPercentage"]; }
46    }
47    #endregion
48
49    #region properties
50    public VariableVector SampleVariableVector {
51      get { return SampleVariableVectorParameter.Value; }
52    }
53    public PercentValue SpreadPercentage {
54      get { return SpreadPercentageParameter.Value; }
55    }
56
57    public VariableVectorActionComparer ConcreteClassifierComparer {
58      get { return new VariableVectorActionComparer(); }
59    }
60    public override IClassifierComparer ClassifierComparer {
61      get { return ConcreteClassifierComparer; }
62    }
63    #endregion
64
65    [StorableConstructor]
66    protected VariableVectorClassificationProblemData(bool deserializing) : base(deserializing) { }
67    protected VariableVectorClassificationProblemData(VariableVectorClassificationProblemData original, Cloner cloner)
68      : base(original, cloner) {
69    }
70    public override IDeepCloneable Clone(Cloner cloner) {
71      return new VariableVectorClassificationProblemData(this, cloner);
72    }
73
74    public VariableVectorClassificationProblemData(Dataset dataset, IEnumerable<string> allowedConditionVariables, IEnumerable<string> allowedActionVariables) :
75      base(dataset, allowedConditionVariables, allowedActionVariables) {
76      Parameters.Add(new ValueParameter<VariableVector>("SampleVariableVector", "", GenerateSampleVariableVector(dataset, AllowedConditionVariables, AllowedActionVariables)));
77      Parameters.Add(new FixedValueParameter<PercentValue>("SpreadPercentage", "", new PercentValue(0.5)));
78    }
79
80    protected override CheckedItemList<StringValue> CheckVariablesForPossibleTargetVariables(Dataset dataset) {
81      var allVariables = GetVariablesOfDataSet(dataset, dataset.VariableNames).Where(v => v is StringVariable || v is IntVariable).Select(v => new StringValue(v.VariableName));
82      return new CheckedItemList<StringValue>(allVariables);
83    }
84
85    private VariableVector GenerateSampleVariableVector(Dataset dataset, IEnumerable<string> allowedConditionVariables, IEnumerable<string> allowedActionVariables) {
86      var conditionVariables = GetVariablesOfDataSet(dataset, allowedConditionVariables);
87      var actionVariables = GetVariablesOfDataSet(dataset, allowedActionVariables);
88      if (!actionVariables.All(x => x is IActionVariable)) {
89        throw new ArgumentException("Action variable can not be empty and all action variables have to be of type int or string.");
90      }
91      return new VariableVector(conditionVariables, actionVariables);
92    }
93
94    private IEnumerable<Encodings.VariableVector.IVariable> GetVariablesOfDataSet(Dataset dataset, IEnumerable<string> allowedVariables) {
95      var variables = new List<HeuristicLab.Encodings.VariableVector.IVariable>();
96      foreach (var variableName in allowedVariables) {
97        var variableValues = dataset.GetValues(variableName);
98        HeuristicLab.Encodings.VariableVector.IVariable variable;
99        if (variableValues is List<string>) {
100          variable = new StringVariable(variableName, (variableValues as List<string>).Distinct());
101        } else if (variableValues is List<double>) {
102          var doubleValues = (variableValues as List<double>).Distinct();
103          if (doubleValues.All(x => x % 1 == 0 || Double.IsNaN(x))) {
104            // ToList call is necessary, because otherwise it wouldn't be possible to serialize it
105            variable = new IntVariable(variableName, doubleValues.Select(x => Convert.ToInt32(x)).ToList());
106          } else {
107            variable = new DoubleVariable(variableName, doubleValues);
108          }
109        } else {
110          throw new ArgumentException("There is no matching variable type for the values in the dataset");
111        }
112        variables.Add(variable);
113      }
114      return variables;
115    }
116
117    public override IInput FetchInput(int rowNumber) {
118      if (!fetchInputCache.ContainsKey(rowNumber)) {
119        VariableVectorInput input = new VariableVectorInput();
120        IEnumerable<string> variableNames = SampleVariableVector.Condition.VariableDictionary.Keys.Union(SampleVariableVector.Action.VariableDictionary.Keys);
121        foreach (var variableName in variableNames) {
122          input.InputDictionary.Add(variableName, Dataset.GetValue(rowNumber, variableName));
123        }
124        fetchInputCache.Add(rowNumber, input);
125      }
126      return fetchInputCache[rowNumber];
127    }
128
129    protected IDictionary<int, IAction> fetchActionCache = new Dictionary<int, IAction>();
130    public override IAction FetchAction(int rowNumber) {
131      if (!fetchActionCache.ContainsKey(rowNumber)) {
132        var action = SampleVariableVector.Action.GetEmptyCopy();
133        foreach (var variableName in action.VariableDictionary.Keys) {
134          action.VariableDictionary[variableName].SetTo(Dataset.GetValue(rowNumber, variableName));
135        }
136        fetchActionCache.Add(rowNumber, action);
137      }
138      return fetchActionCache[rowNumber];
139    }
140
141    protected override void ActionConditionVariablesChanged() {
142      SampleVariableVectorParameter.Value = GenerateSampleVariableVector(Dataset, AllowedConditionVariables, AllowedActionVariables);
143      OnChanged();
144    }
145  }
146}
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