Changeset 15449 for branches/MathNetNumerics-Exploration-2789/HeuristicLab.Algorithms.DataAnalysis.Experimental/Splines.cs

Timestamp:

11/03/17 20:28:37 (6 years ago)

Author:

gkronber

Message:

#2789 created x64 build of CUBGCV algorithm, fixed some bugs

File:

• branches/MathNetNumerics-Exploration-2789/HeuristicLab.Algorithms.DataAnalysis.Experimental/Splines.cs (modified) (6 diffs)

branches/MathNetNumerics-Exploration-2789/HeuristicLab.Algorithms.DataAnalysis.Experimental/Splines.cs

@@ -68 +68 @@
           "Smoothing Spline (Reinsch with automatic tolerance determination using LOOCV)",
           "B-Spline Smoothing",
-          "Penalized Regression Spline (alglib)"
+          "Penalized Regression Spline (alglib)",
+          "CUBGCV"
       }.Select(s => new StringValue(s)));
 
-      Parameters.Add(new ConstrainedValueParameter<StringValue>("Type", "The type of spline (as supported by alglib)", validTypes, validTypes.First()));
+      Parameters.Add(new ConstrainedValueParameter<StringValue>("Type", "The type of spline (as supported by alglib)", validTypes, validTypes.Last()));
       Parameters.Add(new ValueParameter<DoubleValue>("Lambda", "Regularization parameter for smoothing splines (0..+inf)", new DoubleValue(100)));
       Parameters.Add(new ValueParameter<DoubleValue>("StdDev (noise)", "Known error in y values. Used only be Reinsch Smoothing Splines", new DoubleValue(0.1)));
@@ -151 +152 @@
               Results.Add(new Result("Optimal tolerance", new DoubleValue(optTol)));
               Results.Add(new Result("RMSE (LOO-CV)", new DoubleValue(looRMSE)));
+              break;
+            }
+          case "CUBGCV": {
+              CubicSplineGCV.CubGcvReport report;
+              var model = 
+                CubicSplineGCV.CalculateCubicSpline(x, y, 
+                Problem.ProblemData.TargetVariable, inputVars, out report);
+              var targetVar = Problem.ProblemData.TargetVariable;
+              var problemData = (IRegressionProblemData)Problem.ProblemData.Clone();
+              Results.Add(new Result("Solution", model.CreateRegressionSolution(problemData)));
+              Results.Add(new Result("GCV", new DoubleValue(report.generalizedCrossValidation)));
+              Results.Add(new Result("Estimated error variance", new DoubleValue(report.estimatedErrorVariance)));
+              Results.Add(new Result("Estimated RSS degrees of freedom", new DoubleValue(report.estimatedRSSDegreesOfFreedom)));
+              Results.Add(new Result("Estimated treu mean squared error at data points", new DoubleValue(report.estimatedTrueMeanSquaredErrorAtDataPoints)));
+              Results.Add(new Result("Mean square of DF", new DoubleValue(report.meanSquareOfDf)));
+              Results.Add(new Result("Mean square residual", new DoubleValue(report.meanSquareResiudal)));
+              Results.Add(new Result("Smoothing parameter (optimized for GCV)", new DoubleValue(report.smoothingParameter)));
               break;
             }
@@ -489 +507 @@
       }
 
+      // extrapolate for xx > x[n2]
+      b[b.Length] = b[b.Length - 1];
+      d[1] = 0;
+
       return new ReinschSmoothingSplineModel(a, b, c, d, x, targetVar, inputVars);
     }
@@ -550 +572 @@
     }
 
-    private static void SortAndBin(double[] x, double[] y, double[] w, out double[] x2, out double[] y2, out double[] w2, bool scaling = false) {
+    public static void SortAndBin(double[] x, double[] y, double[] w, out double[] x2, out double[] y2, out double[] w2, bool scaling = false) {
       var sortedIdx = Enumerable.Range(0, x.Length).ToArray();
       // sort by x
@@ -679 +701 @@
       this.scale = scale;
       this.offset = offset;
-
-      // extrapolate for xx > x[n2]
-      b[b.Length] = b[b.Length - 1];
-      d[1] = 0;
-      // d[b.Length] = -d[d.Length - 1];
     }
 
@@ -695 +712 @@
 
     public double GetEstimatedValue(double xx) {
-      int n = x.Length;
+      int n = a.Length;
       if (xx <= x[1]) {
         double h = xx - x[1];