[5624] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11310] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5624] | 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.Collections.Generic;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 27 |
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| 28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
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| 29 | /// <summary>
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| 30 | /// Represents a symbolic regression model
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| 31 | /// </summary>
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| 32 | [StorableClass]
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[6555] | 33 | [Item(Name = "Symbolic Regression Model", Description = "Represents a symbolic regression model.")]
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[5624] | 34 | public class SymbolicRegressionModel : SymbolicDataAnalysisModel, ISymbolicRegressionModel {
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| 35 |
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[9587] | 36 |
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[5624] | 37 | [StorableConstructor]
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| 38 | protected SymbolicRegressionModel(bool deserializing) : base(deserializing) { }
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[9587] | 39 | protected SymbolicRegressionModel(SymbolicRegressionModel original, Cloner cloner) : base(original, cloner) { }
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| 40 |
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[5720] | 41 | public SymbolicRegressionModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
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| 42 | double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
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[9587] | 43 | : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) { }
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[5624] | 44 |
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| 45 | public override IDeepCloneable Clone(Cloner cloner) {
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| 46 | return new SymbolicRegressionModel(this, cloner);
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| 47 | }
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| 48 |
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[5649] | 49 | public IEnumerable<double> GetEstimatedValues(Dataset dataset, IEnumerable<int> rows) {
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[5720] | 50 | return Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows)
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[9587] | 51 | .LimitToRange(LowerEstimationLimit, UpperEstimationLimit);
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[5624] | 52 | }
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[5818] | 53 |
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[6603] | 54 | public ISymbolicRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
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[8528] | 55 | return new SymbolicRegressionSolution(this, new RegressionProblemData(problemData));
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[6603] | 56 | }
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| 57 | IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
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| 58 | return CreateRegressionSolution(problemData);
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| 59 | }
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[8972] | 60 |
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| 61 | public void Scale(IRegressionProblemData problemData) {
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| 62 | Scale(problemData, problemData.TargetVariable);
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| 63 | }
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[5624] | 64 | }
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| 65 | }
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