Changeset 12694 for branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs
- Timestamp:
- 07/09/15 13:07:30 (9 years ago)
- Location:
- branches/HeuristicLab.Problems.Orienteering
- Files:
-
- 3 edited
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- Added
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branches/HeuristicLab.Problems.Orienteering
- Property svn:mergeinfo changed
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Property
svn:global-ignores
set to
*.nuget
packages
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branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Problems.DataAnalysis
- Property svn:mergeinfo changed
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branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/DiscriminantFunctionClassificationSolutionBase.cs
r11185 r12694 1 1 #region License Information 2 2 /* HeuristicLab 3 * Copyright (C) 2002-201 4Heuristic and Evolutionary Algorithms Laboratory (HEAL)3 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL) 4 4 * 5 5 * This file is part of HeuristicLab. … … 105 105 TestMeanSquaredError = errorState == OnlineCalculatorError.None ? testMSE : double.NaN; 106 106 107 double trainingR 2 = OnlinePearsonsRSquaredCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);108 TrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR 2: double.NaN;109 double testR 2 = OnlinePearsonsRSquaredCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState);110 TestRSquared = errorState == OnlineCalculatorError.None ? testR 2: double.NaN;107 double trainingR = OnlinePearsonsRCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState); 108 TrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR*trainingR : double.NaN; 109 double testR = OnlinePearsonsRCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState); 110 TestRSquared = errorState == OnlineCalculatorError.None ? testR*testR : double.NaN; 111 111 112 112 double trainingNormalizedGini = NormalizedGiniCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);
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