#region License Information /* HeuristicLab * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; using HeuristicLab.Problems.DataAnalysis; namespace HeuristicLab.Algorithms.DataAnalysis { [Item("PCA", "Initializes the matrix by performing a principal components analysis.")] [StorableClass] public sealed class PcaInitializer : NcaInitializer { [StorableConstructor] private PcaInitializer(bool deserializing) : base(deserializing) { } private PcaInitializer(PcaInitializer original, Cloner cloner) : base(original, cloner) { } public PcaInitializer() : base() { } public override IDeepCloneable Clone(Cloner cloner) { return new PcaInitializer(this, cloner); } public override double[,] Initialize(IClassificationProblemData data, int dimensions) { var instances = data.TrainingIndices.Count(); var attributes = data.AllowedInputVariables.Count(); var pcaDs = data.Dataset.ToArray(data.AllowedInputVariables, data.TrainingIndices); int info; double[] varianceValues; double[,] matrix; alglib.pcabuildbasis(pcaDs, instances, attributes, out info, out varianceValues, out matrix); return matrix; } } }