[8466] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[16140] | 3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[8466] | 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.Linq;
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[9270] | 24 | using HeuristicLab.Algorithms.GradientDescent;
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[8466] | 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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[9270] | 28 | using HeuristicLab.Operators;
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[8466] | 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 32 | using HeuristicLab.PluginInfrastructure;
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| 33 | using HeuristicLab.Problems.DataAnalysis;
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[9270] | 34 | using HeuristicLab.Random;
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[8466] | 35 |
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[8471] | 36 | namespace HeuristicLab.Algorithms.DataAnalysis {
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[8466] | 37 | /// <summary>
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| 38 | /// Neighborhood Components Analysis
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| 39 | /// </summary>
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[8681] | 40 | [Item("Neighborhood Components Analysis (NCA)", @"Implementation of Neighborhood Components Analysis
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| 41 | based on the description of J. Goldberger, S. Roweis, G. Hinton, R. Salakhutdinov. 2005.
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| 42 | Neighbourhood Component Analysis. Advances in Neural Information Processing Systems, 17. pp. 513-520
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| 43 | with additional regularizations described in Z. Yang, J. Laaksonen. 2007.
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| 44 | Regularized Neighborhood Component Analysis. Lecture Notes in Computer Science, 4522. pp. 253-262.")]
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[12504] | 45 | [Creatable(CreatableAttribute.Categories.DataAnalysisClassification, Priority = 170)]
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[8466] | 46 | [StorableClass]
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[9270] | 47 | public sealed class NcaAlgorithm : EngineAlgorithm {
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| 48 | #region Parameter Names
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| 49 | private const string SeedParameterName = "Seed";
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| 50 | private const string SetSeedRandomlyParameterName = "SetSeedRandomly";
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| 51 | private const string KParameterName = "K";
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| 52 | private const string DimensionsParameterName = "Dimensions";
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| 53 | private const string InitializationParameterName = "Initialization";
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| 54 | private const string NeighborSamplesParameterName = "NeighborSamples";
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| 55 | private const string IterationsParameterName = "Iterations";
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| 56 | private const string RegularizationParameterName = "Regularization";
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| 57 | private const string NcaModelCreatorParameterName = "NcaModelCreator";
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| 58 | private const string NcaSolutionCreatorParameterName = "NcaSolutionCreator";
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| 59 | private const string ApproximateGradientsParameterName = "ApproximateGradients";
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| 60 | private const string NcaMatrixParameterName = "NcaMatrix";
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| 61 | private const string NcaMatrixGradientsParameterName = "NcaMatrixGradients";
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| 62 | private const string QualityParameterName = "Quality";
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| 63 | #endregion
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| 64 |
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| 65 | public override Type ProblemType { get { return typeof(IClassificationProblem); } }
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| 66 | public new IClassificationProblem Problem {
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| 67 | get { return (IClassificationProblem)base.Problem; }
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| 68 | set { base.Problem = value; }
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| 69 | }
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| 70 |
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[8466] | 71 | #region Parameter Properties
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[9270] | 72 | public IValueParameter<IntValue> SeedParameter {
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| 73 | get { return (IValueParameter<IntValue>)Parameters[SeedParameterName]; }
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| 74 | }
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| 75 | public IValueParameter<BoolValue> SetSeedRandomlyParameter {
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| 76 | get { return (IValueParameter<BoolValue>)Parameters[SetSeedRandomlyParameterName]; }
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| 77 | }
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[8470] | 78 | public IFixedValueParameter<IntValue> KParameter {
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[9270] | 79 | get { return (IFixedValueParameter<IntValue>)Parameters[KParameterName]; }
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[8466] | 80 | }
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| 81 | public IFixedValueParameter<IntValue> DimensionsParameter {
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[9270] | 82 | get { return (IFixedValueParameter<IntValue>)Parameters[DimensionsParameterName]; }
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[8466] | 83 | }
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[9270] | 84 | public IConstrainedValueParameter<INcaInitializer> InitializationParameter {
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| 85 | get { return (IConstrainedValueParameter<INcaInitializer>)Parameters[InitializationParameterName]; }
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[8466] | 86 | }
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| 87 | public IFixedValueParameter<IntValue> NeighborSamplesParameter {
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[9270] | 88 | get { return (IFixedValueParameter<IntValue>)Parameters[NeighborSamplesParameterName]; }
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[8466] | 89 | }
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| 90 | public IFixedValueParameter<IntValue> IterationsParameter {
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[9270] | 91 | get { return (IFixedValueParameter<IntValue>)Parameters[IterationsParameterName]; }
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[8466] | 92 | }
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[8681] | 93 | public IFixedValueParameter<DoubleValue> RegularizationParameter {
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[9270] | 94 | get { return (IFixedValueParameter<DoubleValue>)Parameters[RegularizationParameterName]; }
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[8681] | 95 | }
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[9270] | 96 | public IValueParameter<BoolValue> ApproximateGradientsParameter {
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| 97 | get { return (IValueParameter<BoolValue>)Parameters[ApproximateGradientsParameterName]; }
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| 98 | }
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| 99 | public IValueParameter<INcaModelCreator> NcaModelCreatorParameter {
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| 100 | get { return (IValueParameter<INcaModelCreator>)Parameters[NcaModelCreatorParameterName]; }
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| 101 | }
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| 102 | public IValueParameter<INcaSolutionCreator> NcaSolutionCreatorParameter {
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| 103 | get { return (IValueParameter<INcaSolutionCreator>)Parameters[NcaSolutionCreatorParameterName]; }
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| 104 | }
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[8466] | 105 | #endregion
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| 106 |
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| 107 | #region Properties
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[9270] | 108 | public int Seed {
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| 109 | get { return SeedParameter.Value.Value; }
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| 110 | set { SeedParameter.Value.Value = value; }
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| 111 | }
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| 112 | public bool SetSeedRandomly {
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| 113 | get { return SetSeedRandomlyParameter.Value.Value; }
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| 114 | set { SetSeedRandomlyParameter.Value.Value = value; }
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| 115 | }
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[8681] | 116 | public int K {
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[8470] | 117 | get { return KParameter.Value.Value; }
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| 118 | set { KParameter.Value.Value = value; }
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[8466] | 119 | }
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[8681] | 120 | public int Dimensions {
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[8466] | 121 | get { return DimensionsParameter.Value.Value; }
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| 122 | set { DimensionsParameter.Value.Value = value; }
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| 123 | }
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[8681] | 124 | public int NeighborSamples {
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[8466] | 125 | get { return NeighborSamplesParameter.Value.Value; }
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| 126 | set { NeighborSamplesParameter.Value.Value = value; }
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| 127 | }
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[8681] | 128 | public int Iterations {
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[8466] | 129 | get { return IterationsParameter.Value.Value; }
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| 130 | set { IterationsParameter.Value.Value = value; }
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| 131 | }
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[8681] | 132 | public double Regularization {
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| 133 | get { return RegularizationParameter.Value.Value; }
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| 134 | set { RegularizationParameter.Value.Value = value; }
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| 135 | }
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[9270] | 136 | public INcaModelCreator NcaModelCreator {
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| 137 | get { return NcaModelCreatorParameter.Value; }
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| 138 | set { NcaModelCreatorParameter.Value = value; }
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| 139 | }
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| 140 | public INcaSolutionCreator NcaSolutionCreator {
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| 141 | get { return NcaSolutionCreatorParameter.Value; }
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| 142 | set { NcaSolutionCreatorParameter.Value = value; }
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| 143 | }
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[8466] | 144 | #endregion
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| 145 |
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| 146 | [StorableConstructor]
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| 147 | private NcaAlgorithm(bool deserializing) : base(deserializing) { }
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| 148 | private NcaAlgorithm(NcaAlgorithm original, Cloner cloner) : base(original, cloner) { }
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| 149 | public NcaAlgorithm()
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| 150 | : base() {
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[9270] | 151 | Parameters.Add(new ValueParameter<IntValue>(SeedParameterName, "The seed of the random number generator.", new IntValue(0)));
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| 152 | Parameters.Add(new ValueParameter<BoolValue>(SetSeedRandomlyParameterName, "A boolean flag that indicates whether the seed should be randomly reset each time the algorithm is run.", new BoolValue(true)));
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| 153 | Parameters.Add(new FixedValueParameter<IntValue>(KParameterName, "The K for the nearest neighbor.", new IntValue(3)));
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| 154 | Parameters.Add(new FixedValueParameter<IntValue>(DimensionsParameterName, "The number of dimensions that NCA should reduce the data to.", new IntValue(2)));
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| 155 | Parameters.Add(new ConstrainedValueParameter<INcaInitializer>(InitializationParameterName, "Which method should be used to initialize the matrix. Typically LDA (linear discriminant analysis) should provide a good estimate."));
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| 156 | Parameters.Add(new FixedValueParameter<IntValue>(NeighborSamplesParameterName, "How many of the neighbors should be sampled in order to speed up the calculation. This should be at least the value of k and at most the number of training instances minus one will be used.", new IntValue(60)));
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| 157 | Parameters.Add(new FixedValueParameter<IntValue>(IterationsParameterName, "How many iterations the conjugate gradient (CG) method should be allowed to perform. The method might still terminate earlier if a local optima has already been reached.", new IntValue(50)));
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| 158 | Parameters.Add(new FixedValueParameter<DoubleValue>(RegularizationParameterName, "A non-negative paramter which can be set to increase generalization and avoid overfitting. If set to 0 the algorithm is similar to NCA as proposed by Goldberger et al.", new DoubleValue(0)));
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| 159 | Parameters.Add(new ValueParameter<INcaModelCreator>(NcaModelCreatorParameterName, "Creates an NCA model out of the matrix.", new NcaModelCreator()));
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| 160 | Parameters.Add(new ValueParameter<INcaSolutionCreator>(NcaSolutionCreatorParameterName, "Creates an NCA solution given a model and some data.", new NcaSolutionCreator()));
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| 161 | Parameters.Add(new ValueParameter<BoolValue>(ApproximateGradientsParameterName, "True if the gradient should be approximated otherwise they are computed exactly.", new BoolValue()));
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[8466] | 162 |
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[9270] | 163 | NcaSolutionCreatorParameter.Hidden = true;
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| 164 | ApproximateGradientsParameter.Hidden = true;
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| 165 |
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| 166 | INcaInitializer defaultInitializer = null;
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| 167 | foreach (var initializer in ApplicationManager.Manager.GetInstances<INcaInitializer>().OrderBy(x => x.ItemName)) {
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| 168 | if (initializer is LdaInitializer) defaultInitializer = initializer;
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[8466] | 169 | InitializationParameter.ValidValues.Add(initializer);
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| 170 | }
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| 171 | if (defaultInitializer != null) InitializationParameter.Value = defaultInitializer;
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| 172 |
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[9270] | 173 | var randomCreator = new RandomCreator();
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| 174 | var ncaInitializer = new Placeholder();
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| 175 | var bfgsInitializer = new LbfgsInitializer();
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| 176 | var makeStep = new LbfgsMakeStep();
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| 177 | var branch = new ConditionalBranch();
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| 178 | var gradientCalculator = new NcaGradientCalculator();
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| 179 | var modelCreator = new Placeholder();
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| 180 | var updateResults = new LbfgsUpdateResults();
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| 181 | var analyzer = new LbfgsAnalyzer();
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| 182 | var finalModelCreator = new Placeholder();
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| 183 | var finalAnalyzer = new LbfgsAnalyzer();
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| 184 | var solutionCreator = new Placeholder();
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[8466] | 185 |
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[9270] | 186 | OperatorGraph.InitialOperator = randomCreator;
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| 187 | randomCreator.SeedParameter.ActualName = SeedParameterName;
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| 188 | randomCreator.SeedParameter.Value = null;
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| 189 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameterName;
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| 190 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 191 | randomCreator.Successor = ncaInitializer;
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[8466] | 192 |
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[9270] | 193 | ncaInitializer.Name = "(NcaInitializer)";
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| 194 | ncaInitializer.OperatorParameter.ActualName = InitializationParameterName;
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| 195 | ncaInitializer.Successor = bfgsInitializer;
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[8681] | 196 |
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[9270] | 197 | bfgsInitializer.IterationsParameter.ActualName = IterationsParameterName;
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| 198 | bfgsInitializer.PointParameter.ActualName = NcaMatrixParameterName;
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| 199 | bfgsInitializer.ApproximateGradientsParameter.ActualName = ApproximateGradientsParameterName;
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| 200 | bfgsInitializer.Successor = makeStep;
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[8466] | 201 |
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[9270] | 202 | makeStep.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
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| 203 | makeStep.PointParameter.ActualName = NcaMatrixParameterName;
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| 204 | makeStep.Successor = branch;
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[8466] | 205 |
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[9270] | 206 | branch.ConditionParameter.ActualName = makeStep.TerminationCriterionParameter.Name;
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| 207 | branch.FalseBranch = gradientCalculator;
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| 208 | branch.TrueBranch = finalModelCreator;
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[8466] | 209 |
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[9270] | 210 | gradientCalculator.Successor = modelCreator;
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[8466] | 211 |
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[9270] | 212 | modelCreator.OperatorParameter.ActualName = NcaModelCreatorParameterName;
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| 213 | modelCreator.Successor = updateResults;
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[8466] | 214 |
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[9270] | 215 | updateResults.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
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| 216 | updateResults.QualityParameter.ActualName = QualityParameterName;
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| 217 | updateResults.QualityGradientsParameter.ActualName = NcaMatrixGradientsParameterName;
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| 218 | updateResults.ApproximateGradientsParameter.ActualName = ApproximateGradientsParameterName;
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| 219 | updateResults.Successor = analyzer;
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[8466] | 220 |
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[9270] | 221 | analyzer.QualityParameter.ActualName = QualityParameterName;
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| 222 | analyzer.PointParameter.ActualName = NcaMatrixParameterName;
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| 223 | analyzer.QualityGradientsParameter.ActualName = NcaMatrixGradientsParameterName;
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| 224 | analyzer.StateParameter.ActualName = bfgsInitializer.StateParameter.Name;
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| 225 | analyzer.PointsTableParameter.ActualName = "Matrix table";
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| 226 | analyzer.QualityGradientsTableParameter.ActualName = "Gradients table";
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| 227 | analyzer.QualitiesTableParameter.ActualName = "Qualities";
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| 228 | analyzer.Successor = makeStep;
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[8466] | 229 |
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[9270] | 230 | finalModelCreator.OperatorParameter.ActualName = NcaModelCreatorParameterName;
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| 231 | finalModelCreator.Successor = finalAnalyzer;
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[8466] | 232 |
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[9270] | 233 | finalAnalyzer.QualityParameter.ActualName = QualityParameterName;
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| 234 | finalAnalyzer.PointParameter.ActualName = NcaMatrixParameterName;
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| 235 | finalAnalyzer.QualityGradientsParameter.ActualName = NcaMatrixGradientsParameterName;
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| 236 | finalAnalyzer.PointsTableParameter.ActualName = analyzer.PointsTableParameter.ActualName;
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| 237 | finalAnalyzer.QualityGradientsTableParameter.ActualName = analyzer.QualityGradientsTableParameter.ActualName;
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| 238 | finalAnalyzer.QualitiesTableParameter.ActualName = analyzer.QualitiesTableParameter.ActualName;
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| 239 | finalAnalyzer.Successor = solutionCreator;
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[8466] | 240 |
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[9270] | 241 | solutionCreator.OperatorParameter.ActualName = NcaSolutionCreatorParameterName;
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[8466] | 242 |
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[9270] | 243 | Problem = new ClassificationProblem();
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[8466] | 244 | }
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| 245 |
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[9270] | 246 | public override IDeepCloneable Clone(Cloner cloner) {
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| 247 | return new NcaAlgorithm(this, cloner);
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[8466] | 248 | }
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| 249 |
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[9270] | 250 | public override void Prepare() {
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| 251 | if (Problem != null) base.Prepare();
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[8466] | 252 | }
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| 253 | }
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| 254 | }
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