- Timestamp:
- 01/15/18 08:21:48 (7 years ago)
- Location:
- branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis
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branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis
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branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4
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/stable/HeuristicLab.Algorithms.DataAnalysis/3.4 merged eligible /trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 merged eligible /branches/1721-RandomForestPersistence/HeuristicLab.Algorithms.DataAnalysis/3.4 10321-10322 /branches/Async/HeuristicLab.Algorithms.DataAnalysis/3.4 13329-15286 /branches/Benchmarking/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 6917-7005 /branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4 9070-13099 /branches/CloningRefactoring/HeuristicLab.Algorithms.DataAnalysis/3.4 4656-4721 /branches/DataAnalysis Refactoring/HeuristicLab.Algorithms.DataAnalysis/3.4 5471-5808 /branches/DataAnalysis SolutionEnsembles/HeuristicLab.Algorithms.DataAnalysis/3.4 5815-6180 /branches/DataAnalysis/HeuristicLab.Algorithms.DataAnalysis/3.4 4458-4459,4462,4464 /branches/DataPreprocessing/HeuristicLab.Algorithms.DataAnalysis/3.4 10085-11101 /branches/GP.Grammar.Editor/HeuristicLab.Algorithms.DataAnalysis/3.4 6284-6795 /branches/GP.Symbols (TimeLag, Diff, Integral)/HeuristicLab.Algorithms.DataAnalysis/3.4 5060 /branches/HeuristicLab.DatasetRefactor/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 11570-12508 /branches/HeuristicLab.Problems.Orienteering/HeuristicLab.Algorithms.DataAnalysis/3.4 11130-12721 /branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis/3.4 13819-14091 /branches/HeuristicLab.TimeSeries/HeuristicLab.Algorithms.DataAnalysis/3.4 8116-8789 /branches/LogResidualEvaluator/HeuristicLab.Algorithms.DataAnalysis/3.4 10202-10483 /branches/NET40/sources/HeuristicLab.Algorithms.DataAnalysis/3.4 5138-5162 /branches/ParallelEngine/HeuristicLab.Algorithms.DataAnalysis/3.4 5175-5192 /branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Algorithms.DataAnalysis/3.4 7773-7810 /branches/QAPAlgorithms/HeuristicLab.Algorithms.DataAnalysis/3.4 6350-6627 /branches/Restructure trunk solution/HeuristicLab.Algorithms.DataAnalysis/3.4 6828 /branches/SpectralKernelForGaussianProcesses/HeuristicLab.Algorithms.DataAnalysis/3.4 10204-10479 /branches/SuccessProgressAnalysis/HeuristicLab.Algorithms.DataAnalysis/3.4 5370-5682 /branches/Trunk/HeuristicLab.Algorithms.DataAnalysis/3.4 6829-6865 /branches/VNS/HeuristicLab.Algorithms.DataAnalysis/3.4 5594-5752 /branches/Weighted TSNE/3.4 15451-15531 /branches/histogram/HeuristicLab.Algorithms.DataAnalysis/3.4 5959-6341 /branches/symbreg-factors-2650/HeuristicLab.Algorithms.DataAnalysis/3.4 14232-14825
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branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestClassification.cs
r14523 r15614 152 152 public static RandomForestClassificationSolution CreateRandomForestClassificationSolution(IClassificationProblemData problemData, int nTrees, double r, double m, int seed, 153 153 out double rmsError, out double relClassificationError, out double outOfBagRmsError, out double outOfBagRelClassificationError) { 154 var model = CreateRandomForestClassificationModel(problemData, nTrees, r, m, seed, out rmsError, out relClassificationError, out outOfBagRmsError, out outOfBagRelClassificationError); 154 var model = CreateRandomForestClassificationModel(problemData, nTrees, r, m, seed, 155 out rmsError, out relClassificationError, out outOfBagRmsError, out outOfBagRelClassificationError); 155 156 return new RandomForestClassificationSolution(model, (IClassificationProblemData)problemData.Clone()); 156 157 } … … 158 159 public static RandomForestModel CreateRandomForestClassificationModel(IClassificationProblemData problemData, int nTrees, double r, double m, int seed, 159 160 out double rmsError, out double relClassificationError, out double outOfBagRmsError, out double outOfBagRelClassificationError) { 160 return RandomForestModel.CreateClassificationModel(problemData, nTrees, r, m, seed, out rmsError, out relClassificationError, out outOfBagRmsError, out outOfBagRelClassificationError); 161 return RandomForestModel.CreateClassificationModel(problemData, nTrees, r, m, seed, 162 rmsError: out rmsError, relClassificationError: out relClassificationError, outOfBagRmsError: out outOfBagRmsError, outOfBagRelClassificationError: out outOfBagRelClassificationError); 161 163 } 162 164 #endregion -
branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestModel.cs
r14843 r15614 288 288 public static RandomForestModel CreateRegressionModel(IRegressionProblemData problemData, int nTrees, double r, double m, int seed, 289 289 out double rmsError, out double outOfBagRmsError, out double avgRelError, out double outOfBagAvgRelError) { 290 return CreateRegressionModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, out rmsError, out avgRelError, out outOfBagAvgRelError, out outOfBagRmsError); 290 return CreateRegressionModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, 291 rmsError: out rmsError, outOfBagRmsError: out outOfBagRmsError, avgRelError: out avgRelError, outOfBagAvgRelError: out outOfBagAvgRelError); 291 292 } 292 293 … … 300 301 301 302 rmsError = rep.rmserror; 303 outOfBagRmsError = rep.oobrmserror; 302 304 avgRelError = rep.avgrelerror; 303 305 outOfBagAvgRelError = rep.oobavgrelerror; 304 outOfBagRmsError = rep.oobrmserror;305 306 306 307 return new RandomForestModel(problemData.TargetVariable, dForest, seed, problemData, nTrees, r, m); … … 309 310 public static RandomForestModel CreateClassificationModel(IClassificationProblemData problemData, int nTrees, double r, double m, int seed, 310 311 out double rmsError, out double outOfBagRmsError, out double relClassificationError, out double outOfBagRelClassificationError) { 311 return CreateClassificationModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, out rmsError, out outOfBagRmsError, out relClassificationError, out outOfBagRelClassificationError); 312 return CreateClassificationModel(problemData, problemData.TrainingIndices, nTrees, r, m, seed, 313 out rmsError, out outOfBagRmsError, out relClassificationError, out outOfBagRelClassificationError); 312 314 } 313 315 -
branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/RandomForest/RandomForestRegression.cs
r14523 r15614 160 160 double r, double m, int seed, 161 161 out double rmsError, out double avgRelError, out double outOfBagRmsError, out double outOfBagAvgRelError) { 162 return RandomForestModel.CreateRegressionModel(problemData, nTrees, r, m, seed, out rmsError, out avgRelError, out outOfBagRmsError, out outOfBagAvgRelError); 162 return RandomForestModel.CreateRegressionModel(problemData, nTrees, r, m, seed, 163 rmsError: out rmsError, avgRelError: out avgRelError, outOfBagRmsError: out outOfBagRmsError, outOfBagAvgRelError: out outOfBagAvgRelError); 163 164 } 164 165
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