Changeset 17120 for branches/2994-AutoDiffForIntervals/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs
- Timestamp:
- 07/10/19 17:39:38 (5 years ago)
- Location:
- branches/2994-AutoDiffForIntervals
- Files:
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- 4 edited
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branches/2994-AutoDiffForIntervals
- Property svn:mergeinfo changed
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branches/2994-AutoDiffForIntervals/HeuristicLab.Algorithms.DataAnalysis
- Property svn:mergeinfo changed
/branches/2435-alglib_3_15/HeuristicLab.Algorithms.DataAnalysis (added) merged: 17034 /trunk/HeuristicLab.Algorithms.DataAnalysis merged: 17030,17032,17037,17043-17044
- Property svn:mergeinfo changed
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branches/2994-AutoDiffForIntervals/HeuristicLab.Algorithms.DataAnalysis/3.4
- Property svn:mergeinfo changed
/branches/2435-alglib_3_15/HeuristicLab.Algorithms.DataAnalysis/3.4 (added) merged: 17034 /trunk/HeuristicLab.Algorithms.DataAnalysis/3.4 merged: 17030,17032,17037,17043-17044
- Property svn:mergeinfo changed
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branches/2994-AutoDiffForIntervals/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesModelSurrogate.cs
r16565 r17120 90 90 private Func<IGradientBoostedTreesModel> CreateLazyInitFunc(IGradientBoostedTreesModel clonedModel) { 91 91 return () => { 92 return clonedModel == null ? RecalculateModel() : clonedModel;92 return clonedModel ?? RecalculateModel(); 93 93 }; 94 94 } 95 95 96 96 // create only the surrogate model without an actual model 97 p ublicGradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed,97 private GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, 98 98 ILossFunction lossFunction, int iterations, int maxSize, double r, double m, double nu) 99 99 : base(trainingProblemData.TargetVariable, "Gradient boosted tree model", string.Empty) { … … 106 106 this.m = m; 107 107 this.nu = nu; 108 109 actualModel = new Lazy<IGradientBoostedTreesModel>(() => RecalculateModel()); 108 110 } 109 111 110 112 // wrap an actual model in a surrograte 111 public GradientBoostedTreesModelSurrogate(IRegressionProblemData trainingProblemData, uint seed, 112 ILossFunction lossFunction, int iterations, int maxSize, double r, double m, double nu, 113 IGradientBoostedTreesModel model) 113 public GradientBoostedTreesModelSurrogate(IGradientBoostedTreesModel model, IRegressionProblemData trainingProblemData, uint seed, 114 ILossFunction lossFunction, int iterations, int maxSize, double r, double m, double nu) 114 115 : this(trainingProblemData, seed, lossFunction, iterations, maxSize, r, m, nu) { 115 116 actualModel = new Lazy<IGradientBoostedTreesModel>(() => model);
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