Changeset 11145 for stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4

Timestamp:

07/08/14 19:29:00 (10 years ago)

Author:

mkommend

Message:

#2143: Merged r10368, r10375, r10378, r10414, r10417, r10418, r10428, r10469, r10470, r11013, r11025, r11026, r11027 into stable.

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningAnalyzer.cs (copied) (copied from trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningAnalyzer.cs) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs (copied) (copied from trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs) (6 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationSolutionImpactValuesCalculator.cs (modified) (4 diffs)

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj

@@ -120 +120 @@
     <Compile Include="ModelCreators\NormalDistributedThresholdsModelCreator.cs" />
     <Compile Include="MultiObjective\SymbolicClassificationMultiObjectiveValidationBestSolutionAnalyzer.cs" />
+    <Compile Include="SymbolicClassificationPruningAnalyzer.cs" />
     <Compile Include="SymbolicClassificationSolutionImpactValuesCalculator.cs" />
     <Compile Include="SymbolicNearestNeighbourClassificationModel.cs" />
@@ -149 +150 @@
       <SubType>Code</SubType>
     </Compile>
+    <Compile Include="SymbolicClassificationPruningOperator.cs" />
     <None Include="HeuristicLab.snk" />
     <None Include="Plugin.cs.frame" />

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningAnalyzer.cs

@@ -1 @@
-using System;
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
@@ -10 +29 @@
   [StorableClass]
   public sealed class SymbolicClassificationPruningAnalyzer : SymbolicDataAnalysisSingleObjectivePruningAnalyzer {
-    private const string ModelCreatorParameterName = "ModelCreator";
-    #region parameter properties
-    public ILookupParameter<ISymbolicClassificationModelCreator> ModelCreatorParameter {
-      get { return (ILookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
-    }
-    #endregion
-    #region properties
-    private ISymbolicClassificationModelCreator ModelCreator {
-      get { return ModelCreatorParameter.ActualValue; }
-      set { ModelCreatorParameter.ActualValue = value; }
-    }
-    #endregion
-
-    protected SymbolicClassificationPruningAnalyzer(SymbolicClassificationPruningAnalyzer original, Cloner cloner)
+    private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";
+    private const string PruningOperatorParameterName = "PruningOperator";
+    private SymbolicClassificationPruningAnalyzer(SymbolicClassificationPruningAnalyzer original, Cloner cloner)
       : base(original, cloner) {
     }
@@ -30 +38 @@
     }
 
+    [StorableConstructor]
+    private SymbolicClassificationPruningAnalyzer(bool deserializing) : base(deserializing) { }
+
     public SymbolicClassificationPruningAnalyzer() {
-      // pruning parameters
-      Parameters.Add(new LookupParameter<ISymbolicClassificationModelCreator>(ModelCreatorParameterName));
-      impactValuesCalculator = new SymbolicClassificationSolutionImpactValuesCalculator();
-    }
-
-    protected override ISymbolicDataAnalysisModel CreateModel(ISymbolicExpressionTree tree,
-      ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = Double.MinValue,
-      double upperEstimationLimit = Double.MaxValue) {
-      var model = ModelCreator.CreateSymbolicClassificationModel(tree, Interpreter, lowerEstimationLimit, upperEstimationLimit);
-      model.RecalculateModelParameters((IClassificationProblemData)ProblemData, ProblemData.TrainingIndices);
-      return model;
+      Parameters.Add(new ValueParameter<SymbolicDataAnalysisSolutionImpactValuesCalculator>(ImpactValuesCalculatorParameterName, "The impact values calculator", new SymbolicClassificationSolutionImpactValuesCalculator()));
+      Parameters.Add(new ValueParameter<SymbolicDataAnalysisExpressionPruningOperator>(PruningOperatorParameterName, "The operator used to prune trees", new SymbolicClassificationPruningOperator()));
     }
   }

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationPruningOperator.cs

@@ -1 @@
-using System.Linq;
+#region License Information
+
+/* HeuristicLab
+ * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+
+#endregion
+
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
-using HeuristicLab.Data;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
@@ -12 +34 @@
     private const string ImpactValuesCalculatorParameterName = "ImpactValuesCalculator";
     private const string ModelCreatorParameterName = "ModelCreator";
-    private const string ApplyLinearScalingParmameterName = "ApplyLinearScaling";
 
     #region parameter properties
@@ -18 +39 @@
       get { return (ILookupParameter<ISymbolicClassificationModelCreator>)Parameters[ModelCreatorParameterName]; }
     }
-
-    public ILookupParameter<BoolValue> ApplyLinearScalingParameter {
-      get { return (ILookupParameter<BoolValue>)Parameters[ApplyLinearScalingParmameterName]; }
-    }
-    #endregion
-    #region properties
-    private ISymbolicClassificationModelCreator ModelCreator { get { return ModelCreatorParameter.ActualValue; } }
-    private BoolValue ApplyLinearScaling { get { return ApplyLinearScalingParameter.ActualValue; } }
     #endregion
 
@@ -31 +44 @@
       : base(original, cloner) {
     }
+
     public override IDeepCloneable Clone(Cloner cloner) {
       return new SymbolicClassificationPruningOperator(this, cloner);
@@ -44 +58 @@
 
     protected override ISymbolicDataAnalysisModel CreateModel() {
-      var model = ModelCreator.CreateSymbolicClassificationModel(SymbolicExpressionTree, Interpreter, EstimationLimits.Lower, EstimationLimits.Upper);
-      var rows = Enumerable.Range(FitnessCalculationPartition.Start, FitnessCalculationPartition.Size);
+      var model = ModelCreatorParameter.ActualValue.CreateSymbolicClassificationModel(SymbolicExpressionTree, Interpreter, EstimationLimits.Lower, EstimationLimits.Upper);
       var problemData = (IClassificationProblemData)ProblemData;
+      var rows = problemData.TrainingIndices;
       model.RecalculateModelParameters(problemData, rows);
       return model;
@@ -54 +68 @@
       var classificationModel = (IClassificationModel)model;
       var classificationProblemData = (IClassificationProblemData)ProblemData;
-      var trainingIndices = ProblemData.TrainingIndices.ToList();
+      var trainingIndices = Enumerable.Range(FitnessCalculationPartition.Start, FitnessCalculationPartition.Size);
       var estimatedValues = classificationModel.GetEstimatedClassValues(ProblemData.Dataset, trainingIndices);
       var targetValues = ProblemData.Dataset.GetDoubleValues(classificationProblemData.TargetVariable, trainingIndices);
       OnlineCalculatorError errorState;
-      var quality = OnlinePearsonsRSquaredCalculator.Calculate(targetValues, estimatedValues, out errorState);
+      var quality = OnlineAccuracyCalculator.Calculate(targetValues, estimatedValues, out errorState);
       if (errorState != OnlineCalculatorError.None) return double.NaN;
       return quality;

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationSolutionImpactValuesCalculator.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using HeuristicLab.Common;
+using HeuristicLab.Core;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
+  [StorableClass]
+  [Item("SymbolicClassificationSolutionImpactValuesCalculator", "Calculate symbolic expression tree node impact values for classification problems.")]
   public class SymbolicClassificationSolutionImpactValuesCalculator : SymbolicDataAnalysisSolutionImpactValuesCalculator {
+    public SymbolicClassificationSolutionImpactValuesCalculator() { }
+    protected SymbolicClassificationSolutionImpactValuesCalculator(SymbolicClassificationSolutionImpactValuesCalculator original, Cloner cloner)
+      : base(original, cloner) { }
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicClassificationSolutionImpactValuesCalculator(this, cloner);
+    }
+    [StorableConstructor]
+    protected SymbolicClassificationSolutionImpactValuesCalculator(bool deserializing) : base(deserializing) { }
+
     public override double CalculateReplacementValue(ISymbolicDataAnalysisModel model, ISymbolicExpressionTreeNode node, IDataAnalysisProblemData problemData, IEnumerable<int> rows) {
       var classificationModel = (ISymbolicClassificationModel)model;
@@ -34 +48 @@
 
     public override double CalculateImpactValue(ISymbolicDataAnalysisModel model, ISymbolicExpressionTreeNode node, IDataAnalysisProblemData problemData, IEnumerable<int> rows, double originalQuality = double.NaN) {
+      double impactValue, replacementValue;
+      CalculateImpactAndReplacementValues(model, node, problemData, rows, out impactValue, out replacementValue, originalQuality);
+      return impactValue;
+    }
+
+    public override void CalculateImpactAndReplacementValues(ISymbolicDataAnalysisModel model, ISymbolicExpressionTreeNode node,
+      IDataAnalysisProblemData problemData, IEnumerable<int> rows, out double impactValue, out double replacementValue,
+      double originalQuality = Double.NaN) {
       var classificationModel = (ISymbolicClassificationModel)model;
       var classificationProblemData = (IClassificationProblemData)problemData;
@@ -47 +69 @@
       }
 
-      var replacementValue = CalculateReplacementValue(classificationModel, node, classificationProblemData, rows);
+      replacementValue = CalculateReplacementValue(classificationModel, node, classificationProblemData, rows);
       var constantNode = new ConstantTreeNode(new Constant()) { Value = replacementValue };
 
@@ -63 +85 @@
       if (errorState != OnlineCalculatorError.None) newQuality = 0.0;
 
-      return originalQuality - newQuality;
+      impactValue = originalQuality - newQuality;
     }
-
   }
 }