Changeset 6569 for branches/QAPAlgorithms/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views
- Timestamp:
- 07/17/11 22:51:11 (13 years ago)
- Location:
- branches/QAPAlgorithms
- Files:
-
- 4 edited
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- Unmodified
- Added
- Removed
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branches/QAPAlgorithms
- Property svn:ignore
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old new 12 12 *.psess 13 13 *.vsp 14 *.docstates
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- Property svn:mergeinfo changed
- Property svn:ignore
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branches/QAPAlgorithms/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views/3.4/HeuristicLabProblemsDataAnalysisSymbolicClassificationViewsPlugin.cs.frame
r5860 r6569 26 26 27 27 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views { 28 [Plugin("HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views","Provides views for symbolic classification problem classes.", "3.4. 0.$WCREV$")]28 [Plugin("HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views","Provides views for symbolic classification problem classes.", "3.4.1.$WCREV$")] 29 29 [PluginFile("HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views-3.4.dll", PluginFileType.Assembly)] 30 30 [PluginDependency("HeuristicLab.Common", "3.3")] -
branches/QAPAlgorithms/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views/3.4/InteractiveSymbolicDiscriminantFunctionClassificationSolutionSimplifierView.cs
r6256 r6569 51 51 protected override void UpdateModel(ISymbolicExpressionTree tree) { 52 52 Content.Model = new SymbolicDiscriminantFunctionClassificationModel(tree, Content.Model.Interpreter); 53 // the default policy for setting thresholds in classification models is the accuarcy maximizing policy 54 // however for performance reasons we must use estimations of the normal distribution cut points as the thresholds 55 // here and in CalculateImpactValues as they are a lot faster to calculate 53 56 Content.SetClassDistibutionCutPointThresholds(); 54 57 } … … 76 79 double[] classValues; 77 80 double[] thresholds; 81 // normal distribution cut points are used as thresholds here because they are a lot faster to calculate than the accuracy maximizing thresholds 78 82 NormalDistributionCutPointsThresholdCalculator.CalculateThresholds(Content.ProblemData, originalOutput, targetClassValues, out classValues, out thresholds); 79 83 var classifier = new SymbolicDiscriminantFunctionClassificationModel(tree, interpreter); -
branches/QAPAlgorithms/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification.Views/3.4/Properties/AssemblyInfo.frame
r5860 r6569 53 53 // by using the '*' as shown below: 54 54 [assembly: AssemblyVersion("3.4.0.0")] 55 [assembly: AssemblyFileVersion("3.4. 0.$WCREV$")]55 [assembly: AssemblyFileVersion("3.4.1.$WCREV$")]
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