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source: branches/WebJobManager/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/ModelCreators/NormalDistributedThresholdsModelCreator.cs @ 15762

Last change on this file since 15762 was 13656, checked in by ascheibe, 9 years ago

#2582 created branch for Hive Web Job Manager

File size: 2.8 KB
Line 
1#region License Information
2
3/* HeuristicLab
4 * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
5 *
6 * This file is part of HeuristicLab.
7 *
8 * HeuristicLab is free software: you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation, either version 3 of the License, or
11 * (at your option) any later version.
12 *
13 * HeuristicLab is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
16 * GNU General Public License for more details.
17 *
18 * You should have received a copy of the GNU General Public License
19 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
20 */
21
22#endregion
23
24using System.Drawing;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
31  [StorableClass]
32  [Item("NormalDistributedThresholdsModelCreator", "")]
33  public sealed class NormalDistributedThresholdsModelCreator : Item, ISymbolicDiscriminantFunctionClassificationModelCreator {
34
35    public override Image ItemImage
36    {
37      get { return HeuristicLab.Common.Resources.VSImageLibrary.Method; }
38    }
39    [StorableConstructor]
40    private NormalDistributedThresholdsModelCreator(bool deserializing) : base(deserializing) { }
41    private NormalDistributedThresholdsModelCreator(NormalDistributedThresholdsModelCreator original, Cloner cloner) : base(original, cloner) { }
42    public NormalDistributedThresholdsModelCreator() : base() { }
43
44    public override IDeepCloneable Clone(Cloner cloner) { return new NormalDistributedThresholdsModelCreator(this, cloner); }
45
46
47    public ISymbolicClassificationModel CreateSymbolicClassificationModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue) {
48      return CreateSymbolicDiscriminantFunctionClassificationModel(tree, interpreter, lowerEstimationLimit, upperEstimationLimit);
49    }
50    public ISymbolicDiscriminantFunctionClassificationModel CreateSymbolicDiscriminantFunctionClassificationModel(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double lowerEstimationLimit = double.MinValue, double upperEstimationLimit = double.MaxValue) {
51      return new SymbolicDiscriminantFunctionClassificationModel(tree, interpreter, new NormalDistributionCutPointsThresholdCalculator(), lowerEstimationLimit, upperEstimationLimit);
52    }
53
54  }
55}
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