Changeset 3452 for trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleNMSEEvaluator.cs

Timestamp:

04/20/10 20:31:23 (14 years ago)

Author:

gkronber

Message:

Included tracking of best of run solution (based on validation set) and calculation of MSE, R² and rel. Error on training and test sets. #938 (Data types and operators for regression problems)

File:

• trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleNMSEEvaluator.cs (copied) (copied from trunk/sources/HeuristicLab.Modeling/3.2/SimpleNMSEEvaluator.cs) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleNMSEEvaluator.cs

@@ -1 @@
-using System;
+#region License Information
+/* HeuristicLab
+ * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ *
+ * This file is part of HeuristicLab.
+ *
+ * HeuristicLab is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * HeuristicLab is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
+ */
+#endregion
+
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -5 +26 @@
 using HeuristicLab.Core;
 using HeuristicLab.Data;
-using HeuristicLab.DataAnalysis;
+using HeuristicLab.Parameters;
 
-namespace HeuristicLab.Modeling {
-  public class SimpleNMSEEvaluator : SimpleEvaluatorBase {
+namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
+  public class SimpleNMSEEvaluator : SimpleEvaluator {
 
-    public override string OutputVariableName {
-      get {
-        return "NMSE";
-      }
-    }
-    public override double Evaluate(double[,] values) {
-      try {
-        return Calculate(values);
-      }
-      catch (ArgumentException) {
-        return double.PositiveInfinity;
-      }
+    public ILookupParameter<DoubleValue> NormalizedMeanSquaredErrorParameter {
+      get { return (ILookupParameter<DoubleValue>)Parameters["NormalizedMeanSquaredError"]; }
     }
 
-    public static double Calculate(double[,] values) {
-      double mse = SimpleMSEEvaluator.Calculate(values);
-      double mean = Statistics.Mean(Matrix<double>.GetColumn(values, ORIGINAL_INDEX));
-      double ssd = 0;
-      int n = 0;
-      for (int i = 0; i < values.GetLength(0); i++) {
-        double original = values[i, ORIGINAL_INDEX];
-        if (!(double.IsNaN(original) || double.IsInfinity(original))) {
-          double dev = original - mean;
-          ssd += dev * dev;
-          n++;
-        }
-      }
-      double variance = ssd / (n - 1);
-      return mse / variance;
+    public SimpleNMSEEvaluator() {
+      Parameters.Add(new LookupParameter<DoubleValue>("NormalizedMeanSquaredError", "The normalized mean squared error (divided by variance) of estimated values."));
+    }
+
+    protected override void Apply(DoubleMatrix values) {
+      var original = from i in Enumerable.Range(0, values.Rows)
+                     select values[i, ORIGINAL_INDEX];
+      var estimated = from i in Enumerable.Range(0, values.Rows)
+                      select values[i, ESTIMATION_INDEX];
+
+      NormalizedMeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(original, estimated));
+    }
+
+    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
+      double mse = SimpleMSEEvaluator.Calculate(original, estimated);
+      return mse / original.Variance();
     }
   }