Changeset 3452 for trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleMeanAbsolutePercentageOfRangeErrorEvaluator.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/SimpleMeanAbsolutePercentageOfRangeErrorEvaluator.cs (copied) (copied from trunk/sources/HeuristicLab.Modeling/3.2/SimpleMeanAbsolutePercentageOfRangeErrorEvaluator.cs) (2 diffs)

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

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -27 +27 @@
 using HeuristicLab.Common;
 using HeuristicLab.Data;
-using HeuristicLab.DataAnalysis;
+using HeuristicLab.Parameters;
 
-namespace HeuristicLab.Modeling {
-  public class SimpleMeanAbsolutePercentageOfRangeErrorEvaluator : SimpleEvaluatorBase {
-    public override string OutputVariableName {
-      get {
-        return "MAPRE";
-      }
+namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
+  public class SimpleMeanAbsolutePercentageOfRangeErrorEvaluator : SimpleEvaluator {
+
+    public ILookupParameter<PercentValue> AveragePercentageOfRangeErrorParameter {
+      get { return (ILookupParameter<PercentValue>)Parameters["AveragePercentageOfRangeError"]; }
     }
 
-    public override double Evaluate(double[,] values) {
-      try {
-        return Calculate(values);
-      }
-      catch (ArgumentException) {
-        return double.PositiveInfinity;
-      }
+    public SimpleMeanAbsolutePercentageOfRangeErrorEvaluator() {
+      Parameters.Add(new LookupParameter<PercentValue>("AveragePercentageOfRangeError", "The average relative (percentage of range) error of estimated values."));
     }
 
-    public static double Calculate(double[,] 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];
+      AveragePercentageOfRangeErrorParameter.ActualValue = new PercentValue(Calculate(original, estimated));
+    }
+
+    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
       double errorsSum = 0.0;
       int n = 0;
-      // copy to one-dimensional array for range calculation
-      double[] originalValues = new double[values.GetLength(0)];
-      for (int i = 0; i < originalValues.Length; i++) originalValues[i] = values[i, ORIGINAL_INDEX];
-      double range = Statistics.Range(originalValues);
-      if (double.IsInfinity(range)) throw new ArgumentException("Range of elements in values is infinity");
-      if (range.IsAlmost(0.0)) throw new ArgumentException("Range of elements in values is zero");
+      IList<double> originalList = original as IList<double>;
+      if (originalList == null) originalList = original.ToList();
 
-      for (int i = 0; i < values.GetLength(0); i++) {
-        double estimated = values[i, ESTIMATION_INDEX];
-        double original = values[i, ORIGINAL_INDEX];
+      double range = originalList.Max() - originalList.Min();
+      if (double.IsInfinity(range)) return double.MaxValue;
+      if (range.IsAlmost(0.0)) return double.MaxValue;
 
-        if (!double.IsNaN(estimated) && !double.IsInfinity(estimated) &&
-          !double.IsNaN(original) && !double.IsInfinity(original) && original != 0.0) {
-          double percent_error = Math.Abs((estimated - original) / range);
+
+      var originalEnumerator = original.GetEnumerator();
+      var estimatedEnumerator = estimated.GetEnumerator();
+      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
+        double e = estimatedEnumerator.Current;
+        double o = originalEnumerator.Current;
+
+        if (!double.IsNaN(e) && !double.IsInfinity(e) &&
+          !double.IsNaN(o) && !double.IsInfinity(o) && !o.IsAlmost(0.0)) {
+          double percent_error = Math.Abs((e - o) / range);
           errorsSum += percent_error;
           n++;
         }
       }
-      if (double.IsInfinity(range) || n == 0) {
-        throw new ArgumentException("Mean of absolute percentage of range error is not defined for input vectors of NaN or Inf");
+      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
+        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
+      } else if (n == 0) {
+        return double.MaxValue;
       } else {
         return errorsSum / n;