#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;
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 : RegressionModel, IClassificationModel, ITimeSeriesPrognosisModel, IStringConvertibleValue {
public override IEnumerable VariablesUsedForPrediction { get { return Enumerable.Empty(); } }
[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;
}
public override IDeepCloneable Clone(Cloner cloner) { return new ConstantModel(this, cloner); }
public ConstantModel(double constant, string targetVariable)
: base(targetVariable) {
this.name = ItemName;
this.description = ItemDescription;
this.constant = constant;
this.ReadOnly = true; // changing a constant regression model is not supported
}
public override 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 override 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
}
#pragma warning disable 0067
public event EventHandler ValueChanged;
#pragma warning restore 0067
#endregion
}
}