#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;
namespace HeuristicLab.Problems.Instances.DataAnalysis {
public class KeijzerFunctionNine : ArtificialRegressionDataDescriptor {
public override string Name { get { return "Keijzer 9 f(x) = arcsinh(x) i.e. ln(x + sqrt(x² + 1))"; } }
public override string Description {
get {
return "Paper: Improving Symbolic Regression with Interval Arithmetic and Linear Scaling" + Environment.NewLine
+ "Authors: Maarten Keijzer" + Environment.NewLine
+ "Function: f(x) = arcsinh(x) i.e. ln(x + sqrt(x² + 1))" + Environment.NewLine
+ "range(train): x = [0:1:100]" + Environment.NewLine
+ "range(test): x = [0:0.1:100]" + Environment.NewLine
+ "Function Set: x + y, x * y, 1/x, -x, sqrt(x)";
}
}
protected override string TargetVariable { get { return "F"; } }
protected override string[] VariableNames { get { return new string[] { "X", "F" }; } }
protected override string[] AllowedInputVariables { get { return new string[] { "X" }; } }
protected override int TrainingPartitionStart { get { return 0; } }
protected override int TrainingPartitionEnd { get { return 101; } }
protected override int TestPartitionStart { get { return 101; } }
protected override int TestPartitionEnd { get { return 1102; } }
protected override List> GenerateValues() {
List> data = new List>();
data.Add(ValueGenerator.GenerateSteps(0m, 100, 1).Select(v => (double)v).ToList());
data[0].AddRange(ValueGenerator.GenerateSteps(0, 100, 0.1m).Select(v => (double)v));
double x;
List results = new List();
for (int i = 0; i < data[0].Count; i++) {
x = data[0][i];
results.Add(Math.Log(x + Math.Sqrt(x * x + 1)));
}
data.Add(results);
return data;
}
}
}