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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/TimeSeriesPrognosis/ITimeSeriesPrognosisSolution.cs @ 6802

Last change on this file since 6802 was 6802, checked in by gkronber, 13 years ago

#1081 added classes (problem, evaluators, analyzers, solution, model, online-calculators, and views) for time series prognosis problems and added an algorithm implementation to generation linear AR (auto-regressive) time series prognosis solution.

File size: 2.1 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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;
23namespace HeuristicLab.Problems.DataAnalysis {
24  public interface ITimeSeriesPrognosisSolution : IDataAnalysisSolution {
25    new ITimeSeriesPrognosisModel Model { get; }
26    new ITimeSeriesPrognosisProblemData ProblemData { get; set; }
27
28    IEnumerable<double> PrognosedTrainingValues { get; }
29    IEnumerable<double> PrognosedTestValues { get; }
30    IEnumerable<double> PrognosedValues { get; }
31    IEnumerable<double> GetPrognosedValues(IEnumerable<int> rows);
32
33    double TrainingMeanSquaredError { get; }
34    double TestMeanSquaredError { get; }
35    double TrainingMeanAbsoluteError { get; }
36    double TestMeanAbsoluteError { get; }
37    double TrainingRSquared { get; }
38    double TestRSquared { get; }
39    double TrainingRelativeError { get; }
40    double TestRelativeError { get; }
41    double TrainingNormalizedMeanSquaredError { get; }
42    double TestNormalizedMeanSquaredError { get; }
43    double TrainingTheilsUStatistic { get; }
44    double TestTheilsUStatistic { get; }
45    double TrainingDirectionalSymmetry { get; }
46    double TestDirectionalSymmetry { get; }
47    double TrainingWeightedDirectionalSymmetry { get; }
48    double TestWeightedDirectionalSymmetry { get; }
49  }                     
50}
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