source: branches/ClassificationModelComparison/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionErrorCharacteristicsCurveView.cs @ 13082

Last change on this file since 13082 was 13082, checked in by gkronber, 7 years ago

#1998: merged changesets r10553:13081 (only on HeuristicLab.Problems.DataAnalysis.Views) from trunk to branch

File size: 2.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 System.Linq;
24using HeuristicLab.MainForm;
25
26namespace HeuristicLab.Problems.DataAnalysis.Views {
27  [View("Error Characteristics Curve")]
28  [Content(typeof(ITimeSeriesPrognosisSolution))]
29  public partial class TimeSeriesPrognosisSolutionErrorCharacteristicsCurveView : RegressionSolutionErrorCharacteristicsCurveView {
30    public TimeSeriesPrognosisSolutionErrorCharacteristicsCurveView()
31      : base() {
32      InitializeComponent();
33    }
34
35    public new ITimeSeriesPrognosisSolution Content {
36      get { return (ITimeSeriesPrognosisSolution)base.Content; }
37      set { base.Content = value; }
38    }
39    public new ITimeSeriesPrognosisProblemData ProblemData {
40      get {
41        if (Content == null) return null;
42        return Content.ProblemData;
43      }
44    }
45
46    protected override IEnumerable<IRegressionSolution> CreateBaselineSolutions() {
47      foreach (var sol in base.CreateBaselineSolutions())
48        yield return sol;
49
50      IEnumerable<double> trainingStartValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Select(r => r - 1).Where(r => r > 0)).ToList();
51      //AR1 model
52      double alpha, beta;
53      OnlineCalculatorError errorState;
54      OnlineLinearScalingParameterCalculator.Calculate(ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Where(x => x > 0)), trainingStartValues, out alpha, out beta, out errorState);
55      var ar1Solution = new TimeSeriesPrognosisAutoRegressiveModel(ProblemData.TargetVariable, new double[] { beta }, alpha).CreateTimeSeriesPrognosisSolution(ProblemData);
56      ar1Solution.Name = "AR(1)";
57      yield return ar1Solution;
58    }
59  }
60}
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