Changeset 13065 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs

Timestamp:

10/26/15 20:44:41 (8 years ago)

Author:

gkronber

Message:

#2450: marked constructor of GBTModel obsolete and wrapped GBTModels in GBTModelSurrogates where necessary in the API. Removed an internal unused method from the API.

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/GradientBoostedTreesAlgorithm.cs

@@ -255 +255 @@
       // produce solution 
       if (CreateSolution) {
-        var surrogateModel = new GradientBoostedTreesModelSurrogate(problemData, (uint)Seed, lossFunction,
-          Iterations, MaxSize, R, M, Nu, state.GetModel());
+        var model = state.GetModel();
 
         // for logistic regression we produce a classification solution
         if (lossFunction is LogisticRegressionLoss) {
-          var model = new DiscriminantFunctionClassificationModel(surrogateModel,
+          var classificationModel = new DiscriminantFunctionClassificationModel(model,
             new AccuracyMaximizationThresholdCalculator());
           var classificationProblemData = new ClassificationProblemData(problemData.Dataset,
             problemData.AllowedInputVariables, problemData.TargetVariable, problemData.Transformations);
-          model.RecalculateModelParameters(classificationProblemData, classificationProblemData.TrainingIndices);
-
-          var classificationSolution = new DiscriminantFunctionClassificationSolution(model, classificationProblemData);
+          classificationModel.RecalculateModelParameters(classificationProblemData, classificationProblemData.TrainingIndices);
+
+          var classificationSolution = new DiscriminantFunctionClassificationSolution(classificationModel, classificationProblemData);
           Results.Add(new Result("Solution", classificationSolution));
         } else {
           // otherwise we produce a regression solution
-          Results.Add(new Result("Solution", new RegressionSolution(surrogateModel, problemData)));
+          Results.Add(new Result("Solution", new RegressionSolution(model, problemData)));
         }
       }