Changeset 2328 for trunk/sources/HeuristicLab.SupportVectorMachines/3.2

Timestamp:

09/03/09 15:00:23 (15 years ago)

Author:

gkronber

Message:

this is the remaining part of changeset r2327.
Applied changes in modeling plugins that are necessary for the new model analyzer (#722)

• predictor has properties for the lower and upper limit of the predicted value
• added views for predictors that show the limits (also added a new view for GeneticProgrammingModel that shows the size and height of the model)
• Reintroduced TreeEvaluatorInjectors that read a PunishmentFactor and calculate the lower and upper limits for estimated values (limits are set in the tree evaluators)
• Added operators to create Predictors. Changed modeling algorithms to use the predictors for the calculation of final model qualities and variable impacts (to be compatible with the new model analyzer the predictors use a very large PunishmentFactor)
• replaced all private implementations of double.IsAlmost and use HL.Commons instead (see #733 r2324)
• Implemented operator SolutionExtractor and moved BestSolutionStorer from HL.Logging to HL.Modeling (fixes #734)

Location:

trunk/sources/HeuristicLab.SupportVectorMachines/3.2

Files:

• HeuristicLab.SupportVectorMachines-3.2.csproj (modified) (2 diffs)
• Predictor.cs (modified) (4 diffs)
• PredictorBuilder.cs (modified) (3 diffs)
• SVMModelView.cs (modified) (1 diff)
• SupportVectorRegression.cs (modified) (1 diff)

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

@@ -83 +83 @@
   </ItemGroup>
   <ItemGroup>
+    <Compile Include="PredictorView.cs">
+      <SubType>UserControl</SubType>
+    </Compile>
+    <Compile Include="PredictorView.Designer.cs">
+      <DependentUpon>PredictorView.cs</DependentUpon>
+    </Compile>
     <Compile Include="Predictor.cs" />
     <Compile Include="PredictorBuilder.cs" />
@@ -154 +160 @@
   </ItemGroup>
   <ItemGroup>
+    <EmbeddedResource Include="PredictorView.resx">
+      <DependentUpon>PredictorView.cs</DependentUpon>
+    </EmbeddedResource>
     <EmbeddedResource Include="SVMModelView.resx">
       <DependentUpon>SVMModelView.cs</DependentUpon>

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

@@ -32 +32 @@
 
 namespace HeuristicLab.SupportVectorMachines {
-  public class Predictor : ItemBase, IPredictor {
+  public class Predictor : PredictorBase {
     private SVMModel svmModel;
+    public SVMModel Model {
+      get { return svmModel; }
+    }
+
     private Dictionary<string, int> variableNames = new Dictionary<string, int>();
     private string targetVariable;
@@ -46 +50 @@
     }
 
-    public double[] Predict(Dataset input, int start, int end) {
+    public override double[] Predict(Dataset input, int start, int end) {
       if (start < 0 || end <= start) throw new ArgumentException("start must be larger than zero and strictly smaller than end");
       if (end > input.Rows) throw new ArgumentOutOfRangeException("number of rows in input is smaller then end");
@@ -64 +68 @@
       double[] result = new double[rows];
       for (int row = 0; row < rows; row++) {
-        result[row] = SVM.Prediction.Predict(model, scaledProblem.X[row]);
+        result[row] = Math.Max(Math.Min(SVM.Prediction.Predict(model, scaledProblem.X[row]), UpperPredictionLimit), LowerPredictionLimit);
       }
       return result;
@@ -70 +74 @@
 
     public override IView CreateView() {
-      return svmModel.CreateView();
+      return new PredictorView(this);
     }
 

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

@@ -37 +37 @@
       AddVariableInfo(new VariableInfo("TargetVariable", "The target variable", typeof(StringData), VariableKind.In));
       AddVariableInfo(new VariableInfo("InputVariables", "The input variable names", typeof(StringData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("TrainingSamplesStart", "Start index of the training set", typeof(IntData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("TrainingSamplesEnd", "End index of the training set", typeof(IntData), VariableKind.In));
+      AddVariableInfo(new VariableInfo("PunishmentFactor", "The punishment factor limits the range of predicted values", typeof(DoubleData), VariableKind.In));
       AddVariableInfo(new VariableInfo("Predictor", "The predictor can be used to generate estimated values", typeof(IPredictor), VariableKind.New));
     }
@@ -48 +51 @@
       SVMModel model = GetVariableValue<SVMModel>("SVMModel", scope, true);
       int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
+      int start = GetVariableValue<IntData>("TrainingSamplesStart", scope, true).Data;
+      int end = GetVariableValue<IntData>("TrainingSamplesEnd", scope, true).Data;
+      double punishmentFactor = GetVariableValue<DoubleData>("PunishmentFactor", scope, true).Data;
+
       string targetVariableName = ds.GetVariableName(targetVariable);
       ItemList inputVariables = GetVariableValue<ItemList>("InputVariables", scope, true);
@@ -53 +60 @@
       for (int i = 0; i < ds.Columns; i++) variableNames[ds.GetVariableName(i)] = i;
 
-      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("Predictor"), new Predictor(model, targetVariableName, variableNames)));
+      double mean = ds.GetMean(targetVariable, start, end);
+      double range = ds.GetRange(targetVariable, start, end);
+
+      Predictor predictor = new Predictor(model, targetVariableName, variableNames);
+      predictor.LowerPredictionLimit = mean - punishmentFactor * range;
+      predictor.UpperPredictionLimit = mean + punishmentFactor * range;
+      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("Predictor"), predictor));
       return null;
     }

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

@@ -33 +33 @@
   public partial class SVMModelView : ViewBase {
     private SVMModel model;
-    
+    public SVMModelView() : base() {
+      InitializeComponent();
+    }    
     public SVMModelView(SVMModel model) : base() {
       InitializeComponent();
       this.model = model;
-      model.Changed += (sender, args) => UpdateControls();
+      model.Changed += (sender, args) => Refresh();
 
-      UpdateControls();
-    }
-
-    protected override void UpdateControls() {
-      base.UpdateControls();
-      numberOfSupportVectors.Text = model.Model.SupportVectorCount.ToString();
-      rho.Text = model.Model.Rho[0].ToString();
-      svmType.Text = model.Model.Parameter.SvmType.ToString();
-      kernelType.Text = model.Model.Parameter.KernelType.ToString();
-      gamma.Text = model.Model.Parameter.Gamma.ToString();
+      numberOfSupportVectors.DataBindings.Add(new Binding("Text", model.Model, "SupportVectorCount"));
+      rho.DataBindings.Add(new Binding("Text", model.Model, "Rho"));
+      svmType.DataBindings.Add(new Binding("Text", model.Model.Parameter, "SvmType"));
+      kernelType.DataBindings.Add(new Binding("Text", model.Model.Parameter, "KernelType"));
+      gamma.DataBindings.Add(new Binding("Text", model.Model.Parameter, "Gamma"));
     }
   }

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

@@ -394 +394 @@
       injector.AddVariable(new HeuristicLab.Core.Variable("KernelType", new StringData("RBF")));
       injector.AddVariable(new HeuristicLab.Core.Variable("Type", new StringData("NU_SVR")));
+      injector.AddVariable(new HeuristicLab.Core.Variable("PunishmentFactor", new DoubleData(1000.0)));
 
       return injector;