Changeset 8732 for trunk/sources

Timestamp:

10/04/12 12:01:26 (12 years ago)

Author:

gkronber

Message:

#1902:

• added caching for variances of GaussianProcessRegressionSolution.
• changed hyperparameter initializers to generate initial values for hyperparameters in a larger range.

Location:

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

Files:

• GaussianProcessHyperparameterInitializer.cs (modified) (1 diff)
• GaussianProcessRegressionSolution.cs (modified) (3 diffs)

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

@@ -91 +91 @@
       var rand = RandomParameter.ActualValue;
       for (int i = 0; i < r.Length; i++)
-        r[i] = rand.NextDouble() * 2 - 1;
+        r[i] = rand.NextDouble() * 10 - 5;
 
       HyperparameterParameter.ActualValue = r;

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

@@ -34 +34 @@
   [StorableClass]
   public sealed class GaussianProcessRegressionSolution : RegressionSolution, IGaussianProcessSolution {
+    private new readonly Dictionary<int, double> evaluationCache;
 
     public new IGaussianProcessModel Model {
@@ -41 +42 @@
 
     [StorableConstructor]
-    private GaussianProcessRegressionSolution(bool deserializing) : base(deserializing) { }
+    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);
     }
     public GaussianProcessRegressionSolution(IGaussianProcessModel model, IRegressionProblemData problemData)
       : base(model, problemData) {
+
+      evaluationCache = new Dictionary<int, double>(problemData.Dataset.Rows);
       RecalculateResults();
     }
@@ -65 +73 @@
 
     public IEnumerable<double> GetEstimatedVariance(IEnumerable<int> rows) {
-      return Model.GetEstimatedVariance(ProblemData.Dataset, 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();
     }
   }