| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2017 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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| 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Collections.Generic;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Optimization;
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| 26 | using HeuristicLab.Problems.DataAnalysis;
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| 27 |
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| 28 | namespace HeuristicLab.Algorithms.DataAnalysis {
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| 29 | internal class M5CreationParameters {
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| 30 | private readonly ISplitType impurity;
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| 31 | private readonly IPruningType pruningType;
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| 32 | private readonly ILeafType<IRegressionModel> leafType;
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| 33 | private readonly int minLeadSize;
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| 34 | private readonly IRegressionProblemData problemData;
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| 35 | private readonly IRandom random;
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| 36 | private readonly ResultCollection results;
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| 37 | public ISplitType Split {
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| 38 | get { return impurity; }
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| 39 | }
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| 40 | public IPruningType Pruningtype {
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| 41 | get { return pruningType; }
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| 42 | }
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| 43 | public ILeafType<IRegressionModel> LeafType {
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| 44 | get { return leafType; }
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| 45 | }
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| 46 | public int MinLeafSize {
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| 47 | get { return minLeadSize; }
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| 48 | }
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| 49 | private IRegressionProblemData ProblemData {
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| 50 | get { return problemData; }
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| 51 | }
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| 52 | public IRandom Random {
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| 53 | get { return random; }
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| 54 | }
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| 55 | public ResultCollection Results {
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| 56 | get { return results; }
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| 57 | }
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| 58 |
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| 59 | public ILeafType<IRegressionModel> PruningLeaf {
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| 60 | get { return Pruningtype.ModelType(LeafType); }
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| 61 | }
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| 62 | public IEnumerable<string> AllowedInputVariables {
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| 63 | get { return ProblemData.AllowedInputVariables; }
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| 64 | }
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| 65 | public string TargetVariable {
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| 66 | get { return ProblemData.TargetVariable; }
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| 67 | }
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| 68 | public IDataset Data {
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| 69 | get { return ProblemData.Dataset; }
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| 70 | }
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| 71 |
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| 72 | public M5CreationParameters(IPruningType pruning, int minleafSize, ILeafType<IRegressionModel> modeltype,
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| 73 | IRegressionProblemData problemData, IRandom random, ISplitType split, ResultCollection results) {
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| 74 | impurity = split;
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| 75 | pruningType = pruning;
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| 76 | this.problemData = problemData;
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| 77 | this.random = random;
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| 78 | leafType = modeltype;
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| 79 | this.results = results;
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| 80 | var pruningLeaf = pruning.ModelType(LeafType);
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| 81 | minLeadSize = Math.Max(pruningLeaf == null ? 0 : pruningLeaf.MinLeafSize(problemData), Math.Max(minleafSize, modeltype.MinLeafSize(problemData)));
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| 82 | }
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| 83 | }
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| 84 | } |
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