Changeset 7759 for branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification

Timestamp:

04/24/12 16:37:40 (13 years ago)

Author:

sforsten

Message:

#1784:

• deleted ClassificationData and RegressionData. RegressionProblemData and ClassificationProblemData are used instead
• deleted not needed Transformer
• ValueGenerator is now a static class and yield return is used return IEnumerable

Location:

branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4

Files:

• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj (modified) (1 diff)
• SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs (modified) (3 diffs)

branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification-3.4.csproj

@@ -196 +196 @@
       <Project>{3D28463F-EC96-4D82-AFEE-38BE91A0CA00}</Project>
       <Name>HeuristicLab.Problems.DataAnalysis.Symbolic-3.4</Name>
+      <Private>False</Private>
     </ProjectReference>
     <ProjectReference Include="..\..\HeuristicLab.Problems.DataAnalysis\3.4\HeuristicLab.Problems.DataAnalysis-3.4.csproj">

branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectiveProblem.cs

@@ -19 +19 @@
  */
 #endregion
-using System;
-using System.Collections.Generic;
 using System.Linq;
 using HeuristicLab.Common;
@@ -33 +31 @@
   [Creatable("Problems")]
   public class SymbolicClassificationSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IClassificationProblemData, ISymbolicClassificationSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IClassificationProblem,
-    IProblemInstanceConsumer<ClassificationData>, IProblemInstanceExporter<ClassificationData> {
+    IProblemInstanceConsumer<ClassificationProblemData>, IProblemInstanceExporter<ClassificationProblemData> {
     private const double PunishmentFactor = 10;
     private const int InitialMaximumTreeDepth = 8;
@@ -113 +111 @@
     }
 
-    public void Load(ClassificationData data) {
+    public void Load(ClassificationProblemData data) {
       Name = data.Name;
       Description = data.Description;
-      Dataset dataset = new Dataset(data.InputVariables, data.Values);
-      ProblemData = new ClassificationProblemData(dataset, data.AllowedInputVariables, data.TargetVariable);
-      ProblemData.TrainingPartition.Start = data.TrainingPartitionStart;
-      ProblemData.TrainingPartition.End = data.TrainingPartitionEnd;
-      ProblemData.TestPartition.Start = data.TestPartitionStart;
-      ProblemData.TestPartition.End = data.TestPartitionEnd;
+      ProblemData = new ClassificationProblemData(data.Dataset, data.AllowedInputVariables, data.TargetVariable);
+      ProblemData.TrainingPartition.Start = data.TrainingPartition.Start;
+      ProblemData.TrainingPartition.End = data.TrainingPartition.End;
+      ProblemData.TestPartition.Start = data.TestPartition.Start;
+      ProblemData.TestPartition.End = data.TestPartition.End;
       OnReset();
     }
 
-    public ClassificationData Export() {
-      if (!ProblemData.InputVariables.Count.Equals(ProblemData.Dataset.DoubleVariables.Count()))
-        throw new ArgumentException("Not all input variables are double variables! (Export only works with double variables)");
-
-      ClassificationData claData = new ClassificationData();
+    public ClassificationProblemData Export() {
+      ClassificationProblemData claData = new ClassificationProblemData(ProblemData.Dataset, ProblemData.AllowedInputVariables, ProblemData.TargetVariable);
       claData.Name = Name;
       claData.Description = Description;
-      claData.TargetVariable = ProblemData.TargetVariable;
-      claData.InputVariables = ProblemData.InputVariables.Select(x => x.Value).ToArray();
-      claData.AllowedInputVariables = ProblemData.AllowedInputVariables.ToArray();
-      claData.TrainingPartitionStart = ProblemData.TrainingPartition.Start;
-      claData.TrainingPartitionEnd = ProblemData.TrainingPartition.End;
-      claData.TestPartitionStart = ProblemData.TestPartition.Start;
-      claData.TestPartitionEnd = ProblemData.TestPartition.End;
-
-      List<List<double>> data = new List<List<double>>();
-      foreach (var variable in ProblemData.Dataset.DoubleVariables) {
-        data.Add(ProblemData.Dataset.GetDoubleValues(variable).ToList());
-      }
-      claData.Values = Transformer.Transformation(data);
-
+      claData.TrainingPartition.Start = ProblemData.TrainingPartition.Start;
+      claData.TrainingPartition.End = ProblemData.TrainingPartition.End;
+      claData.TestPartition.Start = ProblemData.TestPartition.Start;
+      claData.TestPartition.End = ProblemData.TestPartition.End;
       return claData;
     }