Changeset 14095 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4

Timestamp:

07/18/16 15:23:22 (8 years ago)

Author:

mkommend

Message:

#2597: Merged all changesets from HeuristiLab.RegressionSolutionGradientView into the trunk.

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis

Files:

• . (modified) (1 prop)
• 3.4/GaussianProcess/GaussianProcessModel.cs (modified) (1 diff)
• 3.4/GaussianProcess/GaussianProcessRegressionSolution.cs (modified) (3 diffs)
• 3.4/GaussianProcess/StudentTProcessModel.cs (copied) (copied from branches/HeuristicLab.RegressionSolutionGradientView/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/StudentTProcessModel.cs)
• 3.4/GradientBoostedTrees/RegressionTreeBuilder.cs (modified) (2 diffs)
• 3.4/Interfaces/IGaussianProcessModel.cs (modified) (3 diffs)
• 3.4/Interfaces/IGaussianProcessSolution.cs (modified) (1 diff)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessModel.cs

@@ -341 +341 @@
     }
 
-    public IEnumerable<double> GetEstimatedVariance(IDataset dataset, IEnumerable<int> rows) {
+    public IEnumerable<double> GetEstimatedVariances(IDataset dataset, IEnumerable<int> rows) {
       try {
         if (x == null) {

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GaussianProcess/GaussianProcessRegressionSolution.cs

@@ -20 +20 @@
 #endregion
 
-using System.Collections.Generic;
-using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -33 +31 @@
   [Item("GaussianProcessRegressionSolution", "Represents a Gaussian process solution for a regression problem which can be visualized in the GUI.")]
   [StorableClass]
-  public sealed class GaussianProcessRegressionSolution : RegressionSolution, IGaussianProcessSolution {
-    private new readonly Dictionary<int, double> evaluationCache;
+  public sealed class GaussianProcessRegressionSolution : ConfidenceBoundRegressionSolution, IGaussianProcessSolution {
 
     public new IGaussianProcessModel Model {
@@ -44 +41 @@
     private GaussianProcessRegressionSolution(bool deserializing)
       : base(deserializing) {
-      evaluationCache = new Dictionary<int, double>();
-
     }
     private GaussianProcessRegressionSolution(GaussianProcessRegressionSolution original, Cloner cloner)
-      : base(original, cloner) {
-      evaluationCache = new Dictionary<int, double>(original.evaluationCache);
-    }
+      : base(original, cloner) { }
     public GaussianProcessRegressionSolution(IGaussianProcessModel model, IRegressionProblemData problemData)
-      : base(model, problemData) {
-
-      evaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
-    }
+      : base(model, problemData) { }
 
     public override IDeepCloneable Clone(Cloner cloner) {
       return new GaussianProcessRegressionSolution(this, cloner);
     }
-
-    public IEnumerable<double> EstimatedVariance {
-      get { return GetEstimatedVariance(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
-    }
-    public IEnumerable<double> EstimatedTrainingVariance {
-      get { return GetEstimatedVariance(ProblemData.TrainingIndices); }
-    }
-    public IEnumerable<double> EstimatedTestVariance {
-      get { return GetEstimatedVariance(ProblemData.TestIndices); }
-    }
-
-    public IEnumerable<double> GetEstimatedVariance(IEnumerable<int> rows) {
-      var rowsToEvaluate = rows.Except(evaluationCache.Keys);
-      var rowsEnumerator = rowsToEvaluate.GetEnumerator();
-      var valuesEnumerator = Model.GetEstimatedVariance(ProblemData.Dataset, rowsToEvaluate).GetEnumerator();
-
-      while (rowsEnumerator.MoveNext() & valuesEnumerator.MoveNext()) {
-        evaluationCache.Add(rowsEnumerator.Current, valuesEnumerator.Current);
-      }
-
-      return rows.Select(row => evaluationCache[row]);
-    }
-
-    protected override void OnModelChanged() {
-      evaluationCache.Clear();
-      base.OnModelChanged();
-    }
-    protected override void OnProblemDataChanged() {
-      evaluationCache.Clear();
-      base.OnProblemDataChanged();
-    }
   }
 }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/GradientBoostedTrees/RegressionTreeBuilder.cs

@@ -22 +22 @@
 
 using System;
-using System.Collections;
 using System.Collections.Generic;
 using System.Diagnostics;
@@ -129 +128 @@
 
       // y and curPred are changed in gradient boosting
-      this.y = y; 
-      this.curPred = curPred; 
+      this.y = y;
+      this.curPred = curPred;
 
       // shuffle row idx

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Interfaces/IGaussianProcessModel.cs

@@ -20 +20 @@
 #endregion
 
-using System.Collections.Generic;
 using HeuristicLab.Problems.DataAnalysis;
 
@@ -27 +26 @@
   /// Interface to represent a Gaussian process posterior
   /// </summary>
-  public interface IGaussianProcessModel : IRegressionModel {
+  public interface IGaussianProcessModel : IConfidenceBoundRegressionModel {
     double NegativeLogLikelihood { get; }
     double SigmaNoise { get; }
@@ -34 +33 @@
     double[] HyperparameterGradients { get; }
 
-    IEnumerable<double> GetEstimatedVariance(IDataset ds, IEnumerable<int> rows);
     void FixParameters();
   }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/Interfaces/IGaussianProcessSolution.cs

@@ -26 +26 @@
   /// Interface to represent a Gaussian process solution (either regression or classification)
   /// </summary>
-  public interface IGaussianProcessSolution : IDataAnalysisSolution {
+  public interface IGaussianProcessSolution : IConfidenceBoundRegressionSolution {
     new IGaussianProcessModel Model { get; }
   }