Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/SupportVectorMachine/SupportVectorMachineModelCreator.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/SupportVectorMachineModelCreator.cs (modified) (6 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/SupportVectorMachine/SupportVectorMachineModelCreator.cs

@@ -21 +21 @@
 
 using System;
+using System.Collections.Generic;
+using System.Linq;
+using HeuristicLab.Common;
 using HeuristicLab.Core;
 using HeuristicLab.Data;
@@ -34 +37 @@
   [StorableClass]
   [Item("SupportVectorMachineModelCreator", "Represents an operator that creates a support vector machine model.")]
-  public class SupportVectorMachineModelCreator : SingleSuccessorOperator {
+  public sealed class SupportVectorMachineModelCreator : SingleSuccessorOperator {
     private const string DataAnalysisProblemDataParameterName = "DataAnalysisProblemData";
     private const string SvmTypeParameterName = "SvmType";
@@ -108 +111 @@
     #endregion
 
+    [StorableConstructor]
+    private SupportVectorMachineModelCreator(bool deserializing) : base(deserializing) { }
+    private SupportVectorMachineModelCreator(SupportVectorMachineModelCreator original, Cloner cloner) : base(original, cloner) { }
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SupportVectorMachineModelCreator(this, cloner);
+    }
     public SupportVectorMachineModelCreator()
       : base() {
@@ -125 +134 @@
 
     public override IOperation Apply() {
+      int start = SamplesStart.Value;
+      int end = SamplesEnd.Value;
+      IEnumerable<int> rows =
+        Enumerable.Range(start, end - start)
+        .Where(i => i < DataAnalysisProblemData.TestSamplesStart.Value || DataAnalysisProblemData.TestSamplesEnd.Value <= i);
+
       SupportVectorMachineModel model = TrainModel(DataAnalysisProblemData,
-                             SamplesStart.Value, SamplesEnd.Value,
+                             rows,
                              SvmType.Value, KernelType.Value,
                              Cost.Value, Nu.Value, Gamma.Value, Epsilon.Value);
@@ -138 +153 @@
       string svmType, string kernelType,
       double cost, double nu, double gamma, double epsilon) {
-      return TrainModel(problemData, problemData.TrainingSamplesStart.Value, problemData.TrainingSamplesEnd.Value, svmType, kernelType, cost, nu, gamma, epsilon);
+      return TrainModel(problemData, problemData.TrainingIndizes, svmType, kernelType, cost, nu, gamma, epsilon);
     }
 
     public static SupportVectorMachineModel TrainModel(
       DataAnalysisProblemData problemData,
-      int start, int end,
+      IEnumerable<int> trainingIndizes,
       string svmType, string kernelType,
       double cost, double nu, double gamma, double epsilon) {
@@ -160 +175 @@
 
 
-      SVM.Problem problem = SupportVectorMachineUtil.CreateSvmProblem(problemData, start, end);
+      SVM.Problem problem = SupportVectorMachineUtil.CreateSvmProblem(problemData, trainingIndizes);
       SVM.RangeTransform rangeTransform = SVM.RangeTransform.Compute(problem);
       SVM.Problem scaledProblem = Scaling.Scale(rangeTransform, problem);