Changeset 8126

Timestamp:

06/26/12 15:29:45 (12 years ago)

Author:

gkronber

Message:

#1823 fixed a bug in the Pareto-best solution analyzers for symbolic data analysis. Fixed a minor bug in the calculation of classification thresholds, made a sneaky change in SymbolicExpressionTree

Location:

trunk/sources

Files:

• HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/SymbolicExpressionTree.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators/AccuracyMaximizationThresholdCalculator.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Encodings.SymbolicExpressionTreeEncoding/3.4/SymbolicExpressionTree.cs

@@ -23 +23 @@
 using System.Collections.Generic;
 using System.Drawing;
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -77 +78 @@
     public IEnumerable<ISymbolicExpressionTreeNode> IterateNodesBreadth() {
       if (root == null)
-        return new SymbolicExpressionTreeNode[0];
+        return Enumerable.Empty<SymbolicExpressionTreeNode>();
       return root.IterateNodesBreadth();
     }
@@ -83 +84 @@
     public IEnumerable<ISymbolicExpressionTreeNode> IterateNodesPrefix() {
       if (root == null)
-        return new SymbolicExpressionTreeNode[0];
+        return Enumerable.Empty<SymbolicExpressionTreeNode>();
       return root.IterateNodesPrefix();
     }
     public IEnumerable<ISymbolicExpressionTreeNode> IterateNodesPostfix() {
       if (root == null)
-        return new SymbolicExpressionTreeNode[0];
+        return Enumerable.Empty<SymbolicExpressionTreeNode>();
       return root.IterateNodesPostfix();
     }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveTrainingParetoBestSolutionAnalyzer.cs

@@ -100 +100 @@
 
       List<double> complexities;
-      if (ComplexityParameter.ActualValue != null) {
+      if (ComplexityParameter.ActualValue != null && ComplexityParameter.ActualValue.Length == qualities.Count) {
         complexities = ComplexityParameter.ActualValue.Select(x => x.Value).ToList();
       } else {

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveValidationParetoBestSolutionAnalyzer.cs

@@ -137 +137 @@
 
       List<double> complexities;
-      if (ComplexityParameter.ActualValue != null) {
+      if (ComplexityParameter.ActualValue != null && ComplexityParameter.ActualValue.Length == trainingQuality.Length) {
         complexities = ComplexityParameter.ActualValue.Select(x => x.Value).ToList();
       } else {

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ThresholdCalculators/AccuracyMaximizationThresholdCalculator.cs

@@ -54 +54 @@
     public static void CalculateThresholds(IClassificationProblemData problemData, IEnumerable<double> estimatedValues, IEnumerable<double> targetClassValues, out double[] classValues, out double[] thresholds) {
       int slices = 100;
+      double minThresholdInc = 10e-5; // necessary to prevent infinite loop when maxEstimated - minEstimated is effectively zero (constant model)
       List<double> estimatedValuesList = estimatedValues.ToList();
       double maxEstimatedValue = estimatedValuesList.Max();
       double minEstimatedValue = estimatedValuesList.Min();
-      double thresholdIncrement = (maxEstimatedValue - minEstimatedValue) / slices;
+      double thresholdIncrement = Math.Max((maxEstimatedValue - minEstimatedValue) / slices, minThresholdInc);
       var estimatedAndTargetValuePairs =
         estimatedValuesList.Zip(targetClassValues, (x, y) => new { EstimatedValue = x, TargetClassValue = y })
@@ -70 +71 @@
 
       // incrementally calculate accuracy of all possible thresholds
-      int[,] confusionMatrix = new int[nClasses, nClasses];
-
       for (int i = 1; i < thresholds.Length; i++) {
         double lowerThreshold = thresholds[i - 1];