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source: branches/HiveStatistics/sources/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/Regression/IRegressionSolution.cs @ 11359

Last change on this file since 11359 was 11205, checked in by ascheibe, 10 years ago

merged rest of trunk into hive statistics branch

File size: 1.7 KB
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[5496]1#region License Information
2/* HeuristicLab
[11205]3 * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
[5496]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
[5507]22using System.Collections.Generic;
[5496]23namespace HeuristicLab.Problems.DataAnalysis {
[5530]24  public interface IRegressionSolution : IDataAnalysisSolution {
[5496]25    new IRegressionModel Model { get; }
[6653]26    new IRegressionProblemData ProblemData { get; set; }
[5507]27
28    IEnumerable<double> EstimatedValues { get; }
29    IEnumerable<double> EstimatedTrainingValues { get; }
30    IEnumerable<double> EstimatedTestValues { get; }
31    IEnumerable<double> GetEstimatedValues(IEnumerable<int> rows);
[5717]32
33    double TrainingMeanSquaredError { get; }
34    double TestMeanSquaredError { get; }
[6643]35    double TrainingMeanAbsoluteError { get; }
36    double TestMeanAbsoluteError { get; }
[5717]37    double TrainingRSquared { get; }
38    double TestRSquared { get; }
[5829]39    double TrainingRelativeError { get; }
40    double TestRelativeError { get; }
[6588]41    double TrainingNormalizedMeanSquaredError { get; }
42    double TestNormalizedMeanSquaredError { get; }
[5496]43  }
44}
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