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source: stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionSolution.cs @ 18140

Last change on this file since 18140 was 17181, checked in by swagner, 5 years ago

#2875: Merged r17180 from trunk to stable

File size: 1.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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.Collections.Generic;
23using HEAL.Attic;
24
25namespace HeuristicLab.Problems.DataAnalysis {
26  [StorableType("b9d7d1f7-c603-45ef-b372-71b82446fa72")]
27  public interface IRegressionSolution : IDataAnalysisSolution {
28    new IRegressionModel Model { get; }
29    new IRegressionProblemData ProblemData { get; set; }
30
31    IEnumerable<double> EstimatedValues { get; }
32    IEnumerable<double> EstimatedTrainingValues { get; }
33    IEnumerable<double> EstimatedTestValues { get; }
34    IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows);
35
36    double TrainingMeanSquaredError { get; }
37    double TestMeanSquaredError { get; }
38    double TrainingMeanAbsoluteError { get; }
39    double TestMeanAbsoluteError { get; }
40    double TrainingRSquared { get; }
41    double TestRSquared { get; }
42    double TrainingRelativeError { get; }
43    double TestRelativeError { get; }
44    double TrainingNormalizedMeanSquaredError { get; }
45    double TestNormalizedMeanSquaredError { get; }
46    double TrainingRootMeanSquaredError { get; }
47    double TestRootMeanSquaredError { get; }
48  }
49}
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