Changeset 14027 for stable/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers

Timestamp:

07/08/16 14:37:15 (8 years ago)

Author:

mkommend

Message:

#2604: Merged r13826,r13921, r13922, r13941, r13992, r13993, r14000 intos table.

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/OneR.cs (modified) (1 diff)
• HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/OneRClassificationModel.cs (modified) (4 diffs)
• HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/ZeroR.cs (modified) (1 diff)

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/OneR.cs

@@ -139 +139 @@
       }
 
-      var model = new OneRClassificationModel(bestVariable, bestSplits.Select(s => s.thresholdValue).ToArray(), bestSplits.Select(s => s.classValue).ToArray(), bestMissingValuesClass);
+      var model = new OneRClassificationModel(problemData.TargetVariable, bestVariable, bestSplits.Select(s => s.thresholdValue).ToArray(), bestSplits.Select(s => s.classValue).ToArray(), bestMissingValuesClass);
       var solution = new OneRClassificationSolution(model, (IClassificationProblemData)problemData.Clone());
 

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/OneRClassificationModel.cs

@@ -31 +31 @@
   [StorableClass]
   [Item("OneR Classification Model", "A model that uses intervals for one variable to determine the class.")]
-  public class OneRClassificationModel : NamedItem, IClassificationModel {
+  public class OneRClassificationModel : ClassificationModel {
+    public override IEnumerable<string> VariablesUsedForPrediction {
+      get { return new[] { Variable }; }
+    }
+
     [Storable]
     protected string variable;
@@ -66 +70 @@
     public override IDeepCloneable Clone(Cloner cloner) { return new OneRClassificationModel(this, cloner); }
 
-    public OneRClassificationModel(string variable, double[] splits, double[] classes, double missingValuesClass = double.NaN)
-      : base() {
+    public OneRClassificationModel(string targetVariable, string variable, double[] splits, double[] classes, double missingValuesClass = double.NaN)
+      : base(targetVariable) {
       if (splits.Length != classes.Length) {
         throw new ArgumentException("Number of splits and classes has to be equal.");
@@ -84 +88 @@
     // uses sorting to return the values in the order of rows, instead of using nested for loops
     // to avoid O(n²) runtime
-    public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
+    public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
       var values = dataset.GetDoubleValues(Variable, rows).ToArray();
       var rowsArray = rows.ToArray();
@@ -108 +112 @@
     }
 
-    public IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
+    public override IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
       return new OneRClassificationSolution(this, new ClassificationProblemData(problemData));
     }

stable/HeuristicLab.Algorithms.DataAnalysis/3.4/BaselineClassifiers/ZeroR.cs

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