Changeset 5914 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis

Timestamp:

03/31/11 18:23:02 (13 years ago)

Author:

mkommend

Message:

#1418: Changed DataAnalysisSolutions and -Models and updated GenerateRowsToEvaluate method in SymbolicDataAnalysisEvaluator.

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4

Files:

• SupportVectorMachine/SupportVectorClassification.cs (modified) (1 diff)
• SupportVectorMachine/SupportVectorRegression.cs (modified) (1 diff)
• kMeans/KMeansClustering.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorClassification.cs

@@ -142 +142 @@
       var model = new SupportVectorMachineModel(SVM.Training.Train(scaledProblem, parameter), rangeTransform, targetVariable, allowedInputVariables, problemData.ClassValues);
 
-      return new SupportVectorClassificationSolution(model, problemData);
+      return new SupportVectorClassificationSolution(model, (IClassificationProblemData)problemData.Clone());
     }
     #endregion

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/SupportVectorMachine/SupportVectorRegression.cs

@@ -150 +150 @@
       SVM.Problem scaledProblem = SVM.Scaling.Scale(rangeTransform, problem);
       var model = new SupportVectorMachineModel(SVM.Training.Train(scaledProblem, parameter), rangeTransform, targetVariable, allowedInputVariables);
-      return new SupportVectorRegressionSolution(model, problemData);
+      return new SupportVectorRegressionSolution(model, (IRegressionProblemData)problemData.Clone());
     }
     #endregion

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/kMeans/KMeansClustering.cs

@@ -95 +95 @@
       if (info != 1) throw new ArgumentException("Error in calculation of k-Means clustering solution");
 
-      KMeansClusteringSolution solution = new KMeansClusteringSolution(new KMeansClusteringModel(centers, allowedInputVariables), problemData);
+      KMeansClusteringSolution solution = new KMeansClusteringSolution(new KMeansClusteringModel(centers, allowedInputVariables), (IClusteringProblemData)problemData.Clone());
       return solution;
     }