Changeset 13941 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour

Timestamp:

06/28/16 13:33:17 (8 years ago)

Author:

mkommend

Message:

#2604:

• Base classes for data analysis, classification, and regression models
• Added target variable to classification and regression models
• Switched parameter order in data analysis solutions (model, problemdata)

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour

Files:

• NearestNeighbourClassification.cs (modified) (1 diff)
• NearestNeighbourClassificationSolution.cs (modified) (1 diff)
• NearestNeighbourModel.cs (modified) (5 diffs)
• NearestNeighbourRegression.cs (modified) (1 diff)
• NearestNeighbourRegressionSolution.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourClassification.cs

@@ -81 +81 @@
     public static IClassificationSolution CreateNearestNeighbourClassificationSolution(IClassificationProblemData problemData, int k) {
       var problemDataClone = (IClassificationProblemData)problemData.Clone();
-      return new NearestNeighbourClassificationSolution(problemDataClone, Train(problemDataClone, k));
+      return new NearestNeighbourClassificationSolution(Train(problemDataClone, k), problemDataClone);
     }
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourClassificationSolution.cs

@@ -43 +43 @@
       : base(original, cloner) {
     }
-    public NearestNeighbourClassificationSolution(IClassificationProblemData problemData, INearestNeighbourModel nnModel)
+    public NearestNeighbourClassificationSolution(INearestNeighbourModel nnModel, IClassificationProblemData problemData)
       : base(nnModel, problemData) {
     }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourModel.cs

@@ -34 +34 @@
   [StorableClass]
   [Item("NearestNeighbourModel", "Represents a nearest neighbour model for regression and classification.")]
-  public sealed class NearestNeighbourModel : NamedItem, INearestNeighbourModel {
+  public sealed class NearestNeighbourModel : ClassificationModel, INearestNeighbourModel {
 
     private alglib.nearestneighbor.kdtree kdTree;
@@ -48 +48 @@
     }
 
-    public IEnumerable<string> VariablesUsedForPrediction {
+    public override IEnumerable<string> VariablesUsedForPrediction {
       get { return allowedInputVariables; }
     }
 
-    public string TargetVariable {
-      get { return targetVariable; }
-    }
-
-    [Storable]
-    private string targetVariable;
     [Storable]
     private string[] allowedInputVariables;
@@ -99 +93 @@
 
       k = original.k;
-      targetVariable = original.targetVariable;
       allowedInputVariables = (string[])original.allowedInputVariables.Clone();
       if (original.classValues != null)
         this.classValues = (double[])original.classValues.Clone();
     }
-    public NearestNeighbourModel(IDataset dataset, IEnumerable<int> rows, int k, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues = null) {
+    public NearestNeighbourModel(IDataset dataset, IEnumerable<int> rows, int k, string targetVariable, IEnumerable<string> allowedInputVariables, double[] classValues = null)
+      : base(targetVariable) {
       Name = ItemName;
       Description = ItemDescription;
       this.k = k;
-      this.targetVariable = targetVariable;
       this.allowedInputVariables = allowedInputVariables.ToArray();
 
@@ -171 +164 @@
     }
 
-    public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
+    public override IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
       if (classValues == null) throw new InvalidOperationException("No class values are defined.");
       double[,] inputData = AlglibUtil.PrepareInputMatrix(dataset, allowedInputVariables, rows);
@@ -209 +202 @@
     }
 
-    public INearestNeighbourRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
-      return new NearestNeighbourRegressionSolution(new RegressionProblemData(problemData), this);
-    }
+
     IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
-      return CreateRegressionSolution(problemData);
-    }
-    public INearestNeighbourClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
-      return new NearestNeighbourClassificationSolution(new ClassificationProblemData(problemData), this);
-    }
-    IClassificationSolution IClassificationModel.CreateClassificationSolution(IClassificationProblemData problemData) {
-      return CreateClassificationSolution(problemData);
+      return new NearestNeighbourRegressionSolution(this, new RegressionProblemData(problemData));
+    }
+    public override IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
+      return new NearestNeighbourClassificationSolution(this, new ClassificationProblemData(problemData));
     }
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourRegression.cs

@@ -80 +80 @@
     public static IRegressionSolution CreateNearestNeighbourRegressionSolution(IRegressionProblemData problemData, int k) {
       var clonedProblemData = (IRegressionProblemData)problemData.Clone();
-      return new NearestNeighbourRegressionSolution(clonedProblemData, Train(problemData, k));
+      return new NearestNeighbourRegressionSolution(Train(problemData, k), clonedProblemData);
     }
 

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/NearestNeighbour/NearestNeighbourRegressionSolution.cs

@@ -43 +43 @@
       : base(original, cloner) {
     }
-    public NearestNeighbourRegressionSolution(IRegressionProblemData problemData, INearestNeighbourModel nnModel)
+    public NearestNeighbourRegressionSolution(INearestNeighbourModel nnModel, IRegressionProblemData problemData)
       : base(nnModel, problemData) {
     }