Changeset 17035 for branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs
- Timestamp:
- 06/26/19 08:13:50 (5 years ago)
- Location:
- branches/2925_AutoDiffForDynamicalModels
- Files:
-
- 4 edited
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branches/2925_AutoDiffForDynamicalModels
- Property svn:mergeinfo changed
/trunk merged: 17007-17009,17014-17016,17019-17024,17028,17030,17032-17033
- Property svn:mergeinfo changed
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branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis
- Property svn:mergeinfo changed
/trunk/HeuristicLab.Algorithms.DataAnalysis merged: 17030,17032
- Property svn:mergeinfo changed
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branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4
- Property svn:mergeinfo changed
/trunk/HeuristicLab.Algorithms.DataAnalysis/3.4 merged: 17030,17032
- Property svn:mergeinfo changed
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branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithmStatic.cs
r16662 r17035 101 101 102 102 public IRegressionModel GetModel() { 103 #pragma warning disable 618 104 var model = new GradientBoostedTreesModel(models, weights); 105 #pragma warning restore 618 106 // we don't know the number of iterations here but the number of weights is equal 107 // to the number of iterations + 1 (for the constant model) 108 // wrap the actual model in a surrogate that enables persistence and lazy recalculation of the model if necessary 109 return new GradientBoostedTreesModelSurrogate(problemData, randSeed, lossFunction, weights.Count - 1, maxSize, r, m, nu, model); 103 return new GradientBoostedTreesModel(models, weights); 110 104 } 111 105 public IEnumerable<KeyValuePair<string, double>> GetVariableRelevance() {
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