Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Operators/WeightedParentsQualityVarianceComparator.cs

Timestamp:

01/11/11 15:03:46 (13 years ago)

Author:

gkronber

Message:

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

File:

• branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Operators/WeightedParentsQualityVarianceComparator.cs (modified) (4 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Operators/WeightedParentsQualityVarianceComparator.cs

@@ -28 +28 @@
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Common;
 
 namespace HeuristicLab.Problems.DataAnalysis.Operators {
@@ -61 +62 @@
     }
 
+    [StorableConstructor]
+    protected WeightedParentsQualityVarianceComparator(bool deserializing) : base(deserializing) { }
+    protected WeightedParentsQualityVarianceComparator(WeightedParentsQualityVarianceComparator original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public WeightedParentsQualityVarianceComparator()
       : base() {
@@ -75 +81 @@
       Parameters.Add(new ScopeTreeLookupParameter<IntValue>("RightSideSamples", "The number of samples used to calculate the quality of the parent."));
     }
-
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new WeightedParentsQualityVarianceComparator(this, cloner);
+    }
     public override IOperation Apply() {
       double leftQuality = LeftSideParameter.ActualValue.Value;
@@ -114 +122 @@
       double stat = (xmean - ymean) / Math.Sqrt(xvar / n + yvar / m);
       double c = xvar / n / (xvar / n + yvar / m);
-      double df = (n - 1) * (m - 1) / ((m - 1) * AP.Math.Sqr(c) + (n - 1) * (1 - AP.Math.Sqr(c)));
+      double df = (n - 1) * (m - 1) / ((m - 1) * alglib.math.sqr(c) + (n - 1) * (1 - alglib.math.sqr(c)));
       if ((double)(stat) > (double)(0))
-        p = 1 - 0.5 * ibetaf.incompletebeta(df / 2, 0.5, df / (df + AP.Math.Sqr(stat)));
+        p = 1 - 0.5 * alglib.ibetaf.incompletebeta(df / 2, 0.5, df / (df + alglib.math.sqr(stat)));
       else
-        p = 0.5 * ibetaf.incompletebeta(df / 2, 0.5, df / (df + AP.Math.Sqr(stat)));
+        p = 0.5 * alglib.ibetaf.incompletebeta(df / 2, 0.5, df / (df + alglib.math.sqr(stat)));
       double bothtails = 2 * Math.Min(p, 1 - p);
       double lefttail = p;