Changeset 15830 for branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafTypes/LogisticLeaf.cs

Timestamp:

03/08/18 08:46:40 (6 years ago)

Author:

bwerth

Message:

#2847 adapted project to new rep structure; major changes to interfaces; restructures splitting and pruning

File:

• branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafTypes/LogisticLeaf.cs (modified) (2 diffs)

branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafTypes/LogisticLeaf.cs

@@ -33 +33 @@
   [StorableClass]
   [Item("LogisticLeaf", "A leaf type that uses linear models with a logistic dampening as leaf models. Dampening reduces prediction values far outside the observed target values.")]
-  public class LogisticLeaf : ParameterizedNamedItem, ILeafModel {
+  public class LogisticLeaf : LeafBase {
     private const string DampeningParameterName = "Dampening";
     public IFixedValueParameter<DoubleValue> DampeningParameter {
@@ -55 +55 @@
 
     #region IModelType
-    public bool ProvidesConfidence {
+    public override bool ProvidesConfidence {
       get { return true; }
     }
-    public IRegressionModel Build(IRegressionProblemData pd, IRandom random, CancellationToken cancellationToken, out int noParameters) {
-      if (pd.Dataset.Rows < MinLeafSize(pd)) throw new ArgumentException("The number of training instances is too small to create a linear model");
-      double rmse, cvRmse;
-      noParameters = pd.AllowedInputVariables.Count() + 1;
-      return new DampenedLinearModel(PreconstructedLinearModel.CreateConfidenceLinearModel(pd, out rmse, out cvRmse), pd, Dampening);
+    public override IRegressionModel Build(IRegressionProblemData pd, IRandom random, CancellationToken cancellationToken, out int noParameters) {
+      var res = (IConfidenceRegressionModel)new LinearLeaf().Build(pd, random, cancellationToken, out noParameters);
+      return new DampenedLinearModel(res, pd, Dampening);
     }
 
-    public int MinLeafSize(IRegressionProblemData pd) {
+    public override int MinLeafSize(IRegressionProblemData pd) {
       return pd.AllowedInputVariables.Count() + 2;
     }