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source: trunk/sources/HeuristicLab.Modeling/3.3/Model.cs @ 2034

Last change on this file since 2034 was 1906, checked in by gkronber, 15 years ago

Added interface IModel and a standard implementation and changed SVM models to include the range transform in the model. #650 (IAlgorithm and derived interfaces should provide properties to retrieve results)

File size: 1.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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
22using System;
23using System.Collections.Generic;
24using System.Text;
25using HeuristicLab.Core;
26using HeuristicLab.DataAnalysis;
27
28namespace HeuristicLab.Modeling {
29  public class Model : IModel {
30    #region IModel Members
31
32    private Dataset dataset;
33    public Dataset Dataset {
34      get { return dataset; }
35      set { dataset = value; }
36    }
37
38    private string targetVariable;
39    public string TargetVariable {
40      get { return targetVariable; }
41      set { targetVariable = value; }
42    }
43
44    private double trainingMSE;
45    public double TrainingMeanSquaredError {
46      get { return trainingMSE; }
47      set { trainingMSE = value; }
48    }
49
50    private double validationMSE;
51    public double ValidationMeanSquaredError {
52      get { return validationMSE; }
53      set { validationMSE = value; }
54    }
55
56    private double testMSE;
57    public double TestMeanSquaredError {
58      get { return testMSE; }
59      set { testMSE = value; }
60    }
61
62    private IItem data;
63    public IItem Data {
64      get { return data; }
65      set { data = value; }
66    }
67
68    #endregion
69  }
70}
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