source: branches/3136_Structural_GP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/Interfaces/ISymbolicRegressionSingleObjectiveEvaluator.cs @ 18095

Last change on this file since 18095 was 18095, checked in by dpiringe, 2 months ago

#3136

  • added a Evaluate method, which uses the static method Calculate and evaluates a ISymbolicExpressionTree without the need of an ExecutionContext
    • implemented this new method in all single objective SymReg evaluators
File size: 1.6 KB
Line 
1using System.Collections.Generic;
2using System.Linq;
3using HEAL.Attic;
4using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
5#region License Information
6/* HeuristicLab
7 * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
8 *
9 * This file is part of HeuristicLab.
10 *
11 * HeuristicLab is free software: you can redistribute it and/or modify
12 * it under the terms of the GNU General Public License as published by
13 * the Free Software Foundation, either version 3 of the License, or
14 * (at your option) any later version.
15 *
16 * HeuristicLab is distributed in the hope that it will be useful,
17 * but WITHOUT ANY WARRANTY; without even the implied warranty of
18 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
19 * GNU General Public License for more details.
20 *
21 * You should have received a copy of the GNU General Public License
22 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
23 */
24#endregion
25
26namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
27  [StorableType("5dd2601a-b884-48c0-85bc-bc1f437187a3")]
28  public interface ISymbolicRegressionSingleObjectiveEvaluator : ISymbolicRegressionEvaluator, ISymbolicDataAnalysisSingleObjectiveEvaluator<IRegressionProblemData> {
29    double Evaluate(
30      IRegressionProblemData problemData,
31      ISymbolicExpressionTree tree,
32      ISymbolicDataAnalysisExpressionTreeInterpreter interpreter,
33      IEnumerable<int> rows = null,
34      bool applyLinearScaling = true,
35      double lowerEstimationLimit = double.MinValue,
36      double upperEstimationLimit = double.MaxValue);
37  }
38}
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