Changeset 14573 for branches/MemPRAlgorithm/HeuristicLab.Problems.DataAnalysis/3.4/Implementation

Timestamp:

01/15/17 09:57:50 (7 years ago)

Author:

abeham

Message:

#2701:

• changed adaptive walk performance model to relative
• added ConfidenceConstantModel for regression
• using constant model as fallback to GPR
• reorganized code

File:

• branches/MemPRAlgorithm/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ConfidenceConstantModel.cs (copied) (copied from branches/MemPRAlgorithm/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ConstantModel.cs) (4 diffs)

branches/MemPRAlgorithm/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ConfidenceConstantModel.cs

@@ -30 +30 @@
 namespace HeuristicLab.Problems.DataAnalysis {
   [StorableClass]
-  [Item("Constant Model", "A model that always returns the same constant value regardless of the presented input data.")]
-  public class ConstantModel : RegressionModel, IClassificationModel, ITimeSeriesPrognosisModel, IStringConvertibleValue {
+  [Item("Confidence Constant Model", "A model that always returns the same constant mean value and variance regardless of the presented input data.")]
+  public class ConfidenceConstantModel : RegressionModel, IConfidenceRegressionModel, IStringConvertibleValue {
     public override IEnumerable<string> VariablesUsedForPrediction { get { return Enumerable.Empty<string>(); } }
 
@@ -42 +42 @@
     }
 
+    [Storable]
+    private readonly double variance;
+    public double Variance {
+      get { return variance; }
+      // setter not implemented because manipulation of the variance is not allowed
+    }
+
     [StorableConstructor]
-    protected ConstantModel(bool deserializing) : base(deserializing) { }
-    protected ConstantModel(ConstantModel original, Cloner cloner)
+    protected ConfidenceConstantModel(bool deserializing) : base(deserializing) { }
+    protected ConfidenceConstantModel(ConfidenceConstantModel original, Cloner cloner)
       : base(original, cloner) {
       this.constant = original.constant;
+      this.variance = original.variance;
     }
 
-    public override IDeepCloneable Clone(Cloner cloner) { return new ConstantModel(this, cloner); }
+    public override IDeepCloneable Clone(Cloner cloner) { return new ConfidenceConstantModel(this, cloner); }
 
-    public ConstantModel(double constant, string targetVariable)
+    public ConfidenceConstantModel(double constant, double variance, string targetVariable)
       : base(targetVariable) {
       this.name = ItemName;
       this.description = ItemDescription;
       this.constant = constant;
+      this.variance = variance;
       this.ReadOnly = true; // changing a constant regression model is not supported
     }
@@ -62 +71 @@
       return rows.Select(row => Constant);
     }
-    public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
-      return GetEstimatedValues(dataset, rows);
-    }
-    public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
-      return rows.Select(_ => horizons.Select(__ => Constant));
+
+    public IEnumerable<double> GetEstimatedVariances(IDataset dataset, IEnumerable<int> rows) {
+      return rows.Select(x => Variance);
     }
 
     public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
-      return new ConstantRegressionSolution(this, new RegressionProblemData(problemData));
-    }
-    public IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
-      return new ConstantClassificationSolution(this, new ClassificationProblemData(problemData));
-    }
-    public ITimeSeriesPrognosisSolution CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
-      return new TimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData));
+      return new ConfidenceRegressionSolution(this, new RegressionProblemData(problemData));
     }
 
     public override string ToString() {
-      return string.Format("Constant: {0}", GetValue());
+      return string.Format("Constant: {0:E4}, Variance: {1:E4}", Constant, Variance);
     }
 
@@ -101 +102 @@
 #pragma warning restore 0067
     #endregion
-
   }
 }