[3253] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 25 | using System.Drawing;
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| 26 | using HeuristicLab.Common;
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| 27 | using HeuristicLab.Core;
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| 28 | using HeuristicLab.Data;
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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 32 | using HeuristicLab.PluginInfrastructure;
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| 33 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 34 | using HeuristicLab.Problems.DataAnalysis;
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| 35 | using HeuristicLab.Operators;
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| 36 | using HeuristicLab.Problems.DataAnalysis.Evaluators;
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| 37 |
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| 38 | namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
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| 39 | [Item("SymbolicRegressionMeanSquaredErrorEvaluator", "Calculates the mean squared error of a symbolic regression solution.")]
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| 40 | [StorableClass]
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| 41 | public class SymbolicRegressionMeanSquaredErrorEvaluator : SymbolicRegressionEvaluator {
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| 42 | protected override double Evaluate(SymbolicExpressionTree solution, Dataset dataset, StringValue targetVariable, IntValue samplesStart, IntValue samplesEnd, DoubleValue numberOfEvaluatedNodes) {
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| 43 | double mse = Apply(solution, dataset, targetVariable.Value, samplesStart.Value, samplesEnd.Value);
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| 44 | numberOfEvaluatedNodes.Value += solution.Size * (samplesEnd.Value - samplesStart.Value);
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| 45 | return mse;
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| 46 | }
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| 47 |
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| 48 | public static double Apply(SymbolicExpressionTree solution, Dataset dataset, string targetVariable, int start, int end) {
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| 49 | SimpleArithmeticExpressionEvaluator evaluator = new SimpleArithmeticExpressionEvaluator();
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| 50 | var estimatedValues = evaluator.EstimatedValues(solution, dataset, Enumerable.Range(start, end - start));
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| 51 | var originalValues = dataset.VariableValues(targetVariable, start, end);
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| 52 | var values = new DoubleMatrix(MatrixExtensions<double>.Create(estimatedValues.ToArray(), originalValues));
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| 53 | return SimpleMSEEvaluator.Calculate(values);
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| 54 | }
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| 55 | }
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| 56 | }
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