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source: branches/DataAnalysis.PopulationDiversityAnalysis/HeuristicLab.Problems.DataAnalysis.Regression/3.3/LinearRegression/LinearRegressionUtil.cs @ 13475

Last change on this file since 13475 was 4877, checked in by swinkler, 14 years ago

Created branch for population diversity analysis for symbolic regression. (#1278)

File size: 2.4 KB
RevLine 
[4877]1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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;
24
25namespace HeuristicLab.Problems.DataAnalysis.Regression.LinearRegression {
26  public static class LinearRegressionUtil {
27    public static double[,] PrepareInputMatrix(Dataset dataset, string targetVariable, IEnumerable<string> allowedInputVariables, int start, int end) {
28      List<int> allowedRows = CalculateAllowedRows(dataset, targetVariable, allowedInputVariables, start, end);
29
30      double[,] matrix = new double[allowedRows.Count, allowedInputVariables.Count() + 1];
31      for (int row = 0; row < allowedRows.Count; row++) {
32        int col = 0;
33        foreach (string column in allowedInputVariables) {
34          matrix[row, col] = dataset[column, row];
35          col++;
36        }
37        matrix[row, allowedInputVariables.Count()] = dataset[targetVariable, row];
38      }
39      return matrix;
40    }
41
42    private static List<int> CalculateAllowedRows(Dataset dataset, string targetVariable, IEnumerable<string> allowedInputVariables, int start, int end) {
43      List<int> allowedRows = new List<int>();
44      bool add = false;
45
46      for (int row = start; row < end; row++) {
47        add = true;
48        foreach (string column in allowedInputVariables) {
49          double value = dataset[column, row];
50          if (double.IsInfinity(value) ||
51            double.IsNaN(value))
52            add = false;
53        }
54        if (double.IsNaN(dataset[targetVariable, row]))
55          add = false;
56        if (add)
57          allowedRows.Add(row);
58        add = true;
59      }
60      return allowedRows;
61    }
62  }
63}
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