#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) {
}
}
}