Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/SupportVectorMachine/ParameterAdjustmentProblem/SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer.cs

Timestamp:

01/11/11 15:03:46 (13 years ago)

Author:

gkronber

Message:

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

File:

• branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/SupportVectorMachine/ParameterAdjustmentProblem/SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer.cs (modified) (5 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/SupportVectorMachine/ParameterAdjustmentProblem/SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer.cs

@@ -30 +30 @@
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.Problems.DataAnalysis.Evaluators;
+using HeuristicLab.Common;
 
 namespace HeuristicLab.Problems.DataAnalysis.SupportVectorMachine.ParameterAdjustmentProblem {
@@ -89 +90 @@
 
     #endregion
-
+    [StorableConstructor]
+    protected SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
+    protected SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer(SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer()
       : base() {
@@ -103 +108 @@
       Parameters.Add(new LookupParameter<ResultCollection>(ResultsParameterName, "The result collection where the best support vector solution should be stored."));
     }
-
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SupportVectorMachineParameterAdjustmentBestSolutionAnalyzer(this, cloner);
+    }
     public override IOperation Apply() {
       var points = ParameterVectorParameter.ActualValue;
@@ -124 +131 @@
       if (bestModel == null) {
         bestModel = SupportVectorMachineModelCreator.TrainModel(DataAnalysisProblemData,
-          DataAnalysisProblemData.TrainingSamplesStart.Value, DataAnalysisProblemData.TrainingSamplesEnd.Value,
+          DataAnalysisProblemData.TrainingIndizes,
           SvmType.Value, KernelType.Value, cost, nu, gamma, 0.0);
         BestSolutionParameter.ActualValue = bestModel;
@@ -153 +160 @@
         if (BestSolutionQualityParameter.ActualValue.Value > bestQuality) {
           bestModel = SupportVectorMachineModelCreator.TrainModel(DataAnalysisProblemData,
-            DataAnalysisProblemData.TrainingSamplesStart.Value, DataAnalysisProblemData.TrainingSamplesEnd.Value,
+            DataAnalysisProblemData.TrainingIndizes,
             SvmType.Value, KernelType.Value, cost, nu, gamma, 0.0);
           BestSolutionParameter.ActualValue = bestModel;