[5624] | 1 | #region License Information
|
---|
| 2 | /* HeuristicLab
|
---|
[16565] | 3 | * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
|
---|
[5624] | 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 |
|
---|
[14290] | 22 | using System;
|
---|
[5624] | 23 | using System.Collections.Generic;
|
---|
| 24 | using HeuristicLab.Common;
|
---|
| 25 | using HeuristicLab.Core;
|
---|
| 26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
|
---|
[16565] | 27 | using HEAL.Attic;
|
---|
[5624] | 28 |
|
---|
| 29 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
|
---|
| 30 | /// <summary>
|
---|
| 31 | /// Represents a symbolic regression model
|
---|
| 32 | /// </summary>
|
---|
[16565] | 33 | [StorableType("2739C33E-4DDB-4285-9DFB-C056D900B2F2")]
|
---|
[6555] | 34 | [Item(Name = "Symbolic Regression Model", Description = "Represents a symbolic regression model.")]
|
---|
[5624] | 35 | public class SymbolicRegressionModel : SymbolicDataAnalysisModel, ISymbolicRegressionModel {
|
---|
[13921] | 36 | [Storable]
|
---|
[14290] | 37 | private string targetVariable;
|
---|
[13921] | 38 | public string TargetVariable {
|
---|
| 39 | get { return targetVariable; }
|
---|
[14290] | 40 | set {
|
---|
| 41 | if (string.IsNullOrEmpty(value) || targetVariable == value) return;
|
---|
| 42 | targetVariable = value;
|
---|
| 43 | OnTargetVariableChanged(this, EventArgs.Empty);
|
---|
| 44 | }
|
---|
[13921] | 45 | }
|
---|
[5624] | 46 |
|
---|
| 47 | [StorableConstructor]
|
---|
[16565] | 48 | protected SymbolicRegressionModel(StorableConstructorFlag _) : base(_) {
|
---|
[14289] | 49 | targetVariable = string.Empty;
|
---|
| 50 | }
|
---|
[9587] | 51 |
|
---|
[13941] | 52 | protected SymbolicRegressionModel(SymbolicRegressionModel original, Cloner cloner)
|
---|
| 53 | : base(original, cloner) {
|
---|
[13921] | 54 | this.targetVariable = original.targetVariable;
|
---|
| 55 | }
|
---|
[5624] | 56 |
|
---|
[13941] | 57 | public SymbolicRegressionModel(string targetVariable, ISymbolicExpressionTree tree,
|
---|
[13921] | 58 | ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
|
---|
[13941] | 59 | double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue)
|
---|
[13921] | 60 | : base(tree, interpreter, lowerEstimationLimit, upperEstimationLimit) {
|
---|
| 61 | this.targetVariable = targetVariable;
|
---|
| 62 | }
|
---|
| 63 |
|
---|
[5624] | 64 | public override IDeepCloneable Clone(Cloner cloner) {
|
---|
| 65 | return new SymbolicRegressionModel(this, cloner);
|
---|
| 66 | }
|
---|
| 67 |
|
---|
[12509] | 68 | public IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
|
---|
[5720] | 69 | return Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows)
|
---|
[9587] | 70 | .LimitToRange(LowerEstimationLimit, UpperEstimationLimit);
|
---|
[5624] | 71 | }
|
---|
[5818] | 72 |
|
---|
[6603] | 73 | public ISymbolicRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
|
---|
[8528] | 74 | return new SymbolicRegressionSolution(this, new RegressionProblemData(problemData));
|
---|
[6603] | 75 | }
|
---|
| 76 | IRegressionSolution IRegressionModel.CreateRegressionSolution(IRegressionProblemData problemData) {
|
---|
| 77 | return CreateRegressionSolution(problemData);
|
---|
| 78 | }
|
---|
[8972] | 79 |
|
---|
| 80 | public void Scale(IRegressionProblemData problemData) {
|
---|
| 81 | Scale(problemData, problemData.TargetVariable);
|
---|
| 82 | }
|
---|
[14290] | 83 |
|
---|
[16243] | 84 | public virtual bool IsProblemDataCompatible(IRegressionProblemData problemData, out string errorMessage) {
|
---|
| 85 | return RegressionModel.IsProblemDataCompatible(this, problemData, out errorMessage);
|
---|
| 86 | }
|
---|
| 87 |
|
---|
| 88 | public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
|
---|
| 89 | if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
|
---|
| 90 | var regressionProblemData = problemData as IRegressionProblemData;
|
---|
| 91 | if (regressionProblemData == null)
|
---|
[16763] | 92 | throw new ArgumentException("The problem data is not compatible with this symbolic regression model. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
|
---|
[16243] | 93 | return IsProblemDataCompatible(regressionProblemData, out errorMessage);
|
---|
| 94 | }
|
---|
| 95 |
|
---|
[14290] | 96 | #region events
|
---|
| 97 | public event EventHandler TargetVariableChanged;
|
---|
| 98 | private void OnTargetVariableChanged(object sender, EventArgs args) {
|
---|
| 99 | var changed = TargetVariableChanged;
|
---|
| 100 | if (changed != null)
|
---|
| 101 | changed(sender, args);
|
---|
| 102 | }
|
---|
| 103 | #endregion
|
---|
[5624] | 104 | }
|
---|
| 105 | }
|
---|