[645] | 1 | #region License Information
|
---|
| 2 | /* HeuristicLab
|
---|
| 3 | * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
| 4 | *
|
---|
| 5 | * This file is part of HeuristicLab.
|
---|
| 6 | *
|
---|
| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
|
---|
| 8 | * it under the terms of the GNU General Public License as published by
|
---|
| 9 | * the Free Software Foundation, either version 3 of the License, or
|
---|
| 10 | * (at your option) any later version.
|
---|
| 11 | *
|
---|
| 12 | * HeuristicLab is distributed in the hope that it will be useful,
|
---|
| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
|
---|
| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
---|
| 15 | * GNU General Public License for more details.
|
---|
| 16 | *
|
---|
| 17 | * You should have received a copy of the GNU General Public License
|
---|
| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
|
---|
| 19 | */
|
---|
| 20 | #endregion
|
---|
| 21 |
|
---|
| 22 | using System;
|
---|
| 23 | using System.Collections.Generic;
|
---|
| 24 | using System.Linq;
|
---|
| 25 | using System.Text;
|
---|
| 26 | using HeuristicLab.Core;
|
---|
| 27 | using HeuristicLab.Data;
|
---|
| 28 | using HeuristicLab.Operators;
|
---|
| 29 |
|
---|
| 30 | namespace HeuristicLab.GP.StructureIdentification {
|
---|
| 31 | public class CoefficientOfDeterminationEvaluator : GPEvaluatorBase {
|
---|
| 32 | public override string Description {
|
---|
| 33 | get {
|
---|
| 34 | return @"Evaluates 'FunctionTree' for all samples of 'Dataset' and calculates
|
---|
| 35 | the 'coefficient of determination' of estimated values vs. real values of 'TargetVariable'.";
|
---|
| 36 | }
|
---|
| 37 | }
|
---|
| 38 |
|
---|
| 39 | public CoefficientOfDeterminationEvaluator()
|
---|
| 40 | : base() {
|
---|
| 41 | AddVariableInfo(new VariableInfo("R2", "The coefficient of determination of the model", typeof(DoubleData), VariableKind.New));
|
---|
| 42 | }
|
---|
| 43 |
|
---|
[1796] | 44 | public override void Evaluate(IScope scope, ITreeEvaluator evaluator, IFunctionTree tree, HeuristicLab.DataAnalysis.Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {
|
---|
[645] | 45 | double errorsSquaredSum = 0.0;
|
---|
| 46 | double originalDeviationTotalSumOfSquares = 0.0;
|
---|
[702] | 47 | double targetMean = dataset.GetMean(targetVariable, start, end);
|
---|
[1796] | 48 |
|
---|
| 49 | double originalSum = 0.0;
|
---|
| 50 | int n = 0;
|
---|
[712] | 51 | for (int sample = start; sample < end; sample++) {
|
---|
[1796] | 52 | double estimated = evaluator.Evaluate(tree, sample);
|
---|
[712] | 53 | double original = dataset.GetValue(sample, targetVariable);
|
---|
| 54 | if (updateTargetValues) {
|
---|
| 55 | dataset.SetValue(sample, targetVariable, estimated);
|
---|
[702] | 56 | }
|
---|
[712] | 57 | if (!double.IsNaN(original) && !double.IsInfinity(original)) {
|
---|
[645] | 58 | double error = estimated - original;
|
---|
| 59 | errorsSquaredSum += error * error;
|
---|
| 60 |
|
---|
[1796] | 61 | originalSum += original;
|
---|
| 62 | n++;
|
---|
[645] | 63 | }
|
---|
| 64 | }
|
---|
| 65 |
|
---|
[1796] | 66 | double originalMean = originalSum / n;
|
---|
| 67 | for(int sample = start; sample < end; sample++){
|
---|
| 68 | double original = dataset.GetValue(sample, targetVariable);
|
---|
| 69 | if (!double.IsNaN(original) && !double.IsInfinity(original)) {
|
---|
| 70 | original = original - originalMean;
|
---|
| 71 | original = original * original;
|
---|
| 72 | originalDeviationTotalSumOfSquares += original;
|
---|
| 73 | }
|
---|
| 74 | }
|
---|
| 75 |
|
---|
[645] | 76 | double quality = 1 - errorsSquaredSum / originalDeviationTotalSumOfSquares;
|
---|
[712] | 77 | if (quality > 1)
|
---|
[645] | 78 | throw new InvalidProgramException();
|
---|
[712] | 79 | if (double.IsNaN(quality) || double.IsInfinity(quality))
|
---|
[645] | 80 | quality = double.MaxValue;
|
---|
[702] | 81 |
|
---|
| 82 | DoubleData r2 = GetVariableValue<DoubleData>("R2", scope, false, false);
|
---|
[712] | 83 | if (r2 == null) {
|
---|
[702] | 84 | r2 = new DoubleData();
|
---|
| 85 | scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("R2"), r2));
|
---|
| 86 | }
|
---|
| 87 |
|
---|
[645] | 88 | r2.Data = quality;
|
---|
| 89 | }
|
---|
| 90 | }
|
---|
| 91 | }
|
---|