Changeset 13098 for branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers

Timestamp:

11/02/15 21:54:58 (8 years ago)

Author:

gkronber

Message:

#1998:

• introduced new class ConstantModel (to merge ConstantRegressionModel, ConstantClassificationModel and ConstantTimeSeriesModel)
• fixed copyright statements
• tried to unify naming
• added F1 score and Matthew's correlation to classification results collection

Location:

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers

Files:

• OneRClassificationModel.cs (modified) (1 diff)
• OneRClassificationSolution.cs (modified) (1 diff)
• ZeroR.cs (modified) (1 diff)

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/OneRClassificationModel.cs

@@ -30 +30 @@
 namespace HeuristicLab.Algorithms.DataAnalysis {
   [StorableClass]
-  [Item("1R Classification Model", "A model that uses intervals for one variable to determine the class.")]
+  [Item("OneR Classification Model", "A model that uses intervals for one variable to determine the class.")]
   public class OneRClassificationModel : NamedItem, IClassificationModel {
     [Storable]

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/OneRClassificationSolution.cs

@@ -27 +27 @@
 namespace HeuristicLab.Algorithms.DataAnalysis {
   [StorableClass]
-  [Item(Name = "1R Classification Solution", Description = "Represents a 1R classification solution (model + data).")]
+  [Item(Name = "OneR Classification Solution", Description = "Represents a OneR classification solution which uses only a single feature with potentially multiple thresholds for class prediction.")]
   public class OneRClassificationSolution : ClassificationSolution {
     public new OneRClassificationModel Model {

branches/ClassificationModelComparison/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/ZeroR.cs

@@ -64 +64 @@
         .MaxItems(kvp => kvp.Value).Select(x => x.Key).First();
 
-      var model = new ConstantRegressionModel(dominantClass);
-      var solution = new ConstantClassificationSolution(model, (IClassificationProblemData)problemData.Clone());
+      var model = new ConstantModel(dominantClass);
+      var solution = model.CreateClassificationSolution(problemData);
       return solution;
     }