source: branches/M5Regression/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafTypes/LinearLeaf.cs @ 15967

Last change on this file since 15967 was 15967, checked in by bwerth, 14 months ago

#2847 added logistic dampening and some minor changes

File size: 2.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2017 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;
23using System.Linq;
24using System.Threading;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis;
29
30namespace HeuristicLab.Algorithms.DataAnalysis {
31  [StorableClass]
32  [Item("LinearLeaf", "A leaf type that uses linear models as leaf models. This is the standard for M5' regression")]
33  public class LinearLeaf : LeafBase {
34    #region Constructors & Cloning
35    [StorableConstructor]
36    protected LinearLeaf(bool deserializing) : base(deserializing) { }
37    protected LinearLeaf(LinearLeaf original, Cloner cloner) : base(original, cloner) { }
38    public LinearLeaf() { }
39    public override IDeepCloneable Clone(Cloner cloner) {
40      return new LinearLeaf(this, cloner);
41    }
42    #endregion
43
44    #region IModelType
45    public override bool ProvidesConfidence {
46      get { return false; }
47    }
48    public override IRegressionModel Build(IRegressionProblemData pd, IRandom random, CancellationToken cancellationToken, out int noParameters) {
49      if (pd.Dataset.Rows < MinLeafSize(pd)) throw new ArgumentException("The number of training instances is too small to create a linear model");
50      double rmse, cvRmse;
51      noParameters = pd.AllowedInputVariables.Count() + 1;
52      var res = LinearRegression.CreateLinearRegressionSolution(pd, out rmse, out cvRmse);
53      return res.Model;
54    }
55
56    public override int MinLeafSize(IRegressionProblemData pd) {
57      return pd.AllowedInputVariables.Count() == 1 ? 2 : pd.AllowedInputVariables.Count() + 2;
58    }
59    #endregion
60  }
61}
Note: See TracBrowser for help on using the repository browser.