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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Classification/IDiscriminantFunctionClassificationModel.cs @ 8623

Last change on this file since 8623 was 8623, checked in by gkronber, 12 years ago

#1902 implemented LS Gaussian Process classification

File size: 1.7 KB
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[5649]1#region License Information
2/* HeuristicLab
[7259]3 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[5649]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
[6604]22using System;
[5649]23using System.Collections.Generic;
24namespace HeuristicLab.Problems.DataAnalysis {
25  public interface IDiscriminantFunctionClassificationModel : IClassificationModel {
[5736]26    IEnumerable<double> Thresholds { get; }
27    IEnumerable<double> ClassValues { get; }
[8623]28    IDiscriminantFunctionThresholdCalculator ThresholdCalculator { get; }
29    void RecalculateModelParameters(IClassificationProblemData problemData, IEnumerable<int> rows);
[6645]30    // class values and thresholds can only be assigned simultanously
[6604]31    void SetThresholdsAndClassValues(IEnumerable<double> thresholds, IEnumerable<double> classValues);
[5717]32    IEnumerable<double> GetEstimatedValues(Dataset dataset, IEnumerable<int> rows);
33
[5649]34    event EventHandler ThresholdsChanged;
[6604]35
36    IDiscriminantFunctionClassificationSolution CreateDiscriminantFunctionClassificationSolution(IClassificationProblemData problemData);
[5649]37  }
38}
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