#region License Information /* HeuristicLab * Copyright (C) 2002-2015 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; using System.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Persistence.Default.CompositeSerializers.Storable; namespace HeuristicLab.Problems.DataAnalysis { [StorableClass] [Item("Constant Model", "A model that always returns the same constant value regardless of the presented input data.")] public class ConstantModel : NamedItem, IRegressionModel, IClassificationModel, ITimeSeriesPrognosisModel, IStringConvertibleValue { public IEnumerable VariablesUsedForPrediction { get { return Enumerable.Empty(); } } [Storable] private readonly string targetVariable; public string TargetVariable { get { return targetVariable; } } [Storable] private readonly double constant; public double Constant { get { return constant; } // setter not implemented because manipulation of the constant is not allowed } [StorableConstructor] protected ConstantModel(bool deserializing) : base(deserializing) { } protected ConstantModel(ConstantModel original, Cloner cloner) : base(original, cloner) { this.constant = original.constant; this.targetVariable = original.targetVariable; } public override IDeepCloneable Clone(Cloner cloner) { return new ConstantModel(this, cloner); } public ConstantModel(double constant, string targetVariable = "Target") : base() { this.name = ItemName; this.description = ItemDescription; this.constant = constant; this.ReadOnly = true; // changing a constant regression model is not supported this.targetVariable = targetVariable; } public IEnumerable GetEstimatedValues(IDataset dataset, IEnumerable rows) { return rows.Select(row => Constant); } public IEnumerable GetEstimatedClassValues(IDataset dataset, IEnumerable rows) { return GetEstimatedValues(dataset, rows); } public IEnumerable> GetPrognosedValues(IDataset dataset, IEnumerable rows, IEnumerable horizons) { return rows.Select(_ => horizons.Select(__ => Constant)); } public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) { return new ConstantRegressionSolution(this, new RegressionProblemData(problemData)); } public IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) { return new ConstantClassificationSolution(this, new ClassificationProblemData(problemData)); } public ITimeSeriesPrognosisSolution CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) { return new TimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData)); } public override string ToString() { return string.Format("Constant: {0}", GetValue()); } #region IStringConvertibleValue public bool ReadOnly { get; private set; } public bool Validate(string value, out string errorMessage) { throw new NotSupportedException(); // changing a constant regression model is not supported } public string GetValue() { return string.Format("{0:E4}", constant); } public bool SetValue(string value) { throw new NotSupportedException(); // changing a constant regression model is not supported } public event EventHandler ValueChanged; #endregion } }