#region License Information /* HeuristicLab * Copyright (C) 2002-2013 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.Collections.Generic; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Parameters; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.DataAnalysis { [StorableClass] [Item("ClassificationEnsembleProblemData", "Represents an item containing all data defining a classification problem.")] public class ClassificationEnsembleProblemData : ClassificationProblemData { public override bool IsTrainingSample(int index) { return index >= 0 && index < Dataset.Rows && TrainingPartition.Start <= index && index < TrainingPartition.End; } public override bool IsTestSample(int index) { return index >= 0 && index < Dataset.Rows && TestPartition.Start <= index && index < TestPartition.End; } private static readonly ClassificationEnsembleProblemData emptyProblemData; public static new ClassificationEnsembleProblemData EmptyProblemData { get { return emptyProblemData; } } static ClassificationEnsembleProblemData() { var problemData = new ClassificationEnsembleProblemData(); problemData.Parameters.Clear(); problemData.Name = "Empty Classification ProblemData"; problemData.Description = "This ProblemData acts as place holder before the correct problem data is loaded."; problemData.isEmpty = true; problemData.Parameters.Add(new FixedValueParameter(DatasetParameterName, "", new Dataset())); problemData.Parameters.Add(new FixedValueParameter>(InputVariablesParameterName, "")); problemData.Parameters.Add(new FixedValueParameter(TrainingPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly())); problemData.Parameters.Add(new FixedValueParameter(TestPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly())); problemData.Parameters.Add(new ConstrainedValueParameter(TargetVariableParameterName, new ItemSet())); problemData.Parameters.Add(new FixedValueParameter(ClassNamesParameterName, "", new StringMatrix(0, 0).AsReadOnly())); problemData.Parameters.Add(new FixedValueParameter(ClassificationPenaltiesParameterName, "", (DoubleMatrix)new DoubleMatrix(0, 0).AsReadOnly())); emptyProblemData = problemData; } [StorableConstructor] protected ClassificationEnsembleProblemData(bool deserializing) : base(deserializing) { } protected ClassificationEnsembleProblemData(ClassificationEnsembleProblemData original, Cloner cloner) : base(original, cloner) { } public override IDeepCloneable Clone(Cloner cloner) { if (this == emptyProblemData) return emptyProblemData; return new ClassificationEnsembleProblemData(this, cloner); } public ClassificationEnsembleProblemData() : base() { } public ClassificationEnsembleProblemData(IClassificationProblemData classificationProblemData) : base(classificationProblemData.Dataset, classificationProblemData.AllowedInputVariables, classificationProblemData.TargetVariable) { this.TrainingPartition.Start = classificationProblemData.TrainingPartition.Start; this.TrainingPartition.End = classificationProblemData.TrainingPartition.End; this.TestPartition.Start = classificationProblemData.TestPartition.Start; this.TestPartition.End = classificationProblemData.TestPartition.End; } public ClassificationEnsembleProblemData(Dataset dataset, IEnumerable allowedInputVariables, string targetVariable) : base(dataset, allowedInputVariables, targetVariable) { } } }