Changeset 13724 for trunk/sources

Timestamp:

03/24/16 11:05:12 (9 years ago)

Author:

mkommend

Message:

#2591: Reversed merged accidentally commited changes to GradientBoostingRegressionAlgorithm (r13721).

File:

• trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GBM/GradientBoostingRegressionAlgorithm.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GBM/GradientBoostingRegressionAlgorithm.cs

@@ -317 +317 @@
           // just produce an ensemble solution for now (TODO: correct scaling or linear regression for ensemble model weights)
 
-          var ensembleSolution = CreateEnsembleSolution(models, (IRegressionProblemData)problemData.Clone());
+          var ensembleModel = new RegressionEnsembleModel(models) { AverageModelEstimates = false };
+          var ensembleSolution = ensembleModel.CreateRegressionSolution((IRegressionProblemData)problemData.Clone());
           Results.Add(new Result("EnsembleSolution", ensembleSolution));
         }
@@ -325 +326 @@
         alg.Prepare(true);
       }
-    }
-
-    private static IRegressionEnsembleSolution CreateEnsembleSolution(List<IRegressionModel> models,
-      IRegressionProblemData problemData) {
-      var rows = problemData.TrainingPartition.Size;
-      var features = models.Count;
-      double[,] inputMatrix = new double[rows, features + 1];
-
-      //add model estimates
-      for (int m = 0; m < models.Count; m++) {
-        var model = models[m];
-        var estimates = model.GetEstimatedValues(problemData.Dataset, problemData.TrainingIndices);
-        int estimatesCounter = 0;
-        foreach (var estimate in estimates) {
-          inputMatrix[estimatesCounter, m] = estimate;
-          estimatesCounter++;
-        }
-      }
-
-      //add target
-      var targets = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices);
-      int targetCounter = 0;
-      foreach (var target in targets) {
-        inputMatrix[targetCounter, models.Count] = target;
-        targetCounter++;
-      }
-
-      alglib.linearmodel lm = new alglib.linearmodel();
-      alglib.lrreport ar = new alglib.lrreport();
-      double[] coefficients;
-      int retVal = 1;
-      alglib.lrbuildz(inputMatrix, rows, features, out retVal, out lm, out ar);
-      if (retVal != 1) throw new ArgumentException("Error in calculation of linear regression solution");
-
-      alglib.lrunpack(lm, out coefficients, out features);
-
-      var ensembleModel = new RegressionEnsembleModel(models, coefficients.Take(models.Count)) { AverageModelEstimates = false };
-      var ensembleSolution = ensembleModel.CreateRegressionSolution((IRegressionProblemData)problemData.Clone());
-      return ensembleSolution;
     }