Changeset 2285 for trunk/sources/HeuristicLab.SupportVectorMachines

Timestamp:

08/13/09 17:28:07 (15 years ago)

Author:

gkronber

Message:

Worked on #722 (IModel should provide a Predict() method to get predicted values for an input vector).
At the same time removed parameter PunishmentFactor from GP algorithms (this parameter is internal to TreeEvaluators now).

Location:

trunk/sources/HeuristicLab.SupportVectorMachines/3.2

Files:

• HeuristicLab.SupportVectorMachines-3.2.csproj (modified) (1 diff)
• Predictor.cs (added)
• SVMHelper.cs (modified) (1 diff)
• SupportVectorRegression.cs (modified) (6 diffs)

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/HeuristicLab.SupportVectorMachines-3.2.csproj

@@ -83 +83 @@
   </ItemGroup>
   <ItemGroup>
+    <Compile Include="Predictor.cs" />
     <Compile Include="SupportVectorRegression.cs" />
     <Compile Include="SVMModel.cs" />

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SVMHelper.cs

@@ -37 +37 @@
             double value = dataset.GetValue(start + row, col);
             if (!double.IsNaN(value))
-              tempRow.Add(new SVM.Node(col, value));
+              tempRow.Add(new SVM.Node(col + 1, value));
           }
         }

trunk/sources/HeuristicLab.SupportVectorMachines/3.2/SupportVectorRegression.cs

@@ -69 +69 @@
     }
 
-    public IModel Model {
+    public IAnalyzerModel Model {
       get {
         if (!engine.Terminated) throw new InvalidOperationException("The algorithm is still running. Wait until the algorithm is terminated to retrieve the result.");
@@ -421 +421 @@
 
 
-    protected internal virtual Model CreateSVMModel(IScope bestModelScope) {
-      Model model = new Model();
+    protected internal virtual IAnalyzerModel CreateSVMModel(IScope bestModelScope) {
+      AnalyzerModel model = new AnalyzerModel();
       model.TrainingMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("Quality", false).Data;
       model.ValidationMeanSquaredError = bestModelScope.GetVariableValue<DoubleData>("ValidationQuality", false).Data;
@@ -439 +439 @@
       model.TestVarianceAccountedFor = bestModelScope.GetVariableValue<DoubleData>("TestVAF", false).Data;
 
-      model.Data = bestModelScope.GetVariableValue<SVMModel>("Model", false);
       HeuristicLab.DataAnalysis.Dataset ds = bestModelScope.GetVariableValue<Dataset>("Dataset", true);
       model.Dataset = ds;
@@ -449 +448 @@
       model.TestSamplesStart = bestModelScope.GetVariableValue<IntData>("TestSamplesStart", true).Data;
       model.TestSamplesEnd = bestModelScope.GetVariableValue<IntData>("TestSamplesEnd", true).Data;
+      model.Predictor = new Predictor(bestModelScope.GetVariableValue<SVMModel>("Model", false), model.TargetVariable);
+
 
       ItemList evaluationImpacts = bestModelScope.GetVariableValue<ItemList>("VariableEvaluationImpacts", false);
@@ -456 +457 @@
         double impact = ((DoubleData)row[1]).Data;
         model.SetVariableEvaluationImpact(variableName, impact);
-        model.AddInputVariables(variableName);
+        model.AddInputVariable(variableName);
       }
       foreach (ItemList row in qualityImpacts) {
@@ -462 +463 @@
         double impact = ((DoubleData)row[1]).Data;
         model.SetVariableQualityImpact(variableName, impact);
-        model.AddInputVariables(variableName);
+        model.AddInputVariable(variableName);
       }