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source: branches/2994-AutoDiffForIntervals/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Classification/UCI/Mammography.cs

Last change on this file was 17209, checked in by gkronber, 5 years ago

#2994: merged r17132:17198 from trunk to branch

File size: 3.2 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
22
23using System;
24namespace HeuristicLab.Problems.Instances.DataAnalysis {
25  public class Mammography : UCIDataDescriptor {
26    public override string Filename { get { return "Mammography"; } }
27    public override string Description {
28      get {
29        return "Data Set Information: Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass."
30        + "Website: http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29" + Environment.NewLine
31        + "Attribute Information:" + Environment.NewLine
32        + "1) ID number" + Environment.NewLine
33        + "2) Diagnosis (M = malignant, B = benign)" + Environment.NewLine
34        + "3-32)" + Environment.NewLine + Environment.NewLine
35        + "Ten real-valued features are computed for each cell nucleus:" + Environment.NewLine + Environment.NewLine
36        + "a) radius (mean of distances from center to points on the perimeter)" + Environment.NewLine
37        + "b) texture (standard deviation of gray-scale values)" + Environment.NewLine
38        + "c) perimeter" + Environment.NewLine
39        + "d) area" + Environment.NewLine
40        + "e) smoothness (local variation in radius lengths)" + Environment.NewLine
41        + "f) compactness (perimeter^2 / area - 1.0)" + Environment.NewLine
42        + "g) concavity (severity of concave portions of the contour)" + Environment.NewLine
43        + "h) concave points (number of concave portions of the contour)" + Environment.NewLine
44        + "i) symmetry" + Environment.NewLine
45        + "j) fractal dimension (\"coastline approximation\" - 1)";
46      }
47    }
48    public override string Donor { get { return "M. Elter"; } }
49    public override int Year { get { return 2007; } }
50
51    protected override string TargetVariable { get { return "Severity"; } }
52    protected override string[] VariableNames {
53      get { return new string[] { "BI-RADS", "Age", "Shape", "Margin", "Density", "Severity" }; }
54    }
55    protected override string[] AllowedInputVariables {
56      get { return new string[] { "BI-RADS", "Age", "Shape", "Margin", "Density" }; }
57    }
58    protected override int TrainingPartitionStart { get { return 0; } }
59    protected override int TrainingPartitionEnd { get { return 641; } }
60    protected override int TestPartitionStart { get { return 641; } }
61    protected override int TestPartitionEnd { get { return 961; } }
62  }
63}
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