public void GradientBoostingTestTowerRelativeError()
{
var gbt = new GradientBoostedTreesAlgorithm();
var provider = new HeuristicLab.Problems.Instances.DataAnalysis.RegressionRealWorldInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name.Contains("Tower"));
var regProblem = new RegressionProblem();
regProblem.Load(provider.LoadData(instance));
#region Algorithm Configuration
gbt.Problem = regProblem;
gbt.Seed = 0;
gbt.SetSeedRandomly = false;
gbt.Iterations = 3000;
gbt.MaxSize = 20;
gbt.Nu = 0.005;
gbt.LossFunctionParameter.Value = gbt.LossFunctionParameter.ValidValues.First(l => l.ToString().Contains("Relative"));
gbt.CreateSolution = false;
#endregion
gbt.Start();
Console.WriteLine(gbt.ExecutionTime);
Assert.AreEqual(0.061954221604374943, ((DoubleValue)gbt.Results["Loss (train)"].Value).Value, 1E-6);
Assert.AreEqual(0.06316303473499961, ((DoubleValue)gbt.Results["Loss (test)"].Value).Value, 1E-6);
}
public void GradientBoostingTestTowerAbsoluteError()
{
var gbt = new GradientBoostedTreesAlgorithm();
var provider = new HeuristicLab.Problems.Instances.DataAnalysis.RegressionRealWorldInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name.Contains("Tower"));
var regProblem = new RegressionProblem();
regProblem.Load(provider.LoadData(instance));
#region Algorithm Configuration
gbt.Problem = regProblem;
gbt.Seed = 0;
gbt.SetSeedRandomly = false;
gbt.Iterations = 1000;
gbt.MaxSize = 20;
gbt.Nu = 0.02;
gbt.LossFunctionParameter.Value = gbt.LossFunctionParameter.ValidValues.First(l => l.ToString().Contains("Absolute"));
gbt.ModelCreation = GradientBoostedTrees.ModelCreation.QualityOnly;
#endregion
gbt.Start();
Console.WriteLine(gbt.ExecutionTime);
Assert.AreEqual(10.551385044666661, ((DoubleValue)gbt.Results["Loss (train)"].Value).Value, 1E-6);
Assert.AreEqual(12.918001745581172, ((DoubleValue)gbt.Results["Loss (test)"].Value).Value, 1E-6);
}
public void GradientBoostingTestTowerSquaredError()
{
var gbt = new GradientBoostedTreesAlgorithm();
var provider = new HeuristicLab.Problems.Instances.DataAnalysis.RegressionRealWorldInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name.Contains("Tower"));
var regProblem = new RegressionProblem();
regProblem.Load(provider.LoadData(instance));
#region Algorithm Configuration
gbt.Problem = regProblem;
gbt.Seed = 0;
gbt.SetSeedRandomly = false;
gbt.Iterations = 5000;
gbt.MaxSize = 20;
gbt.CreateSolution = false;
#endregion
gbt.Start();
Console.WriteLine(gbt.ExecutionTime);
Assert.AreEqual(267.68704241153921, ((DoubleValue)gbt.Results["Loss (train)"].Value).Value, 1E-6);
Assert.AreEqual(393.84704062205469, ((DoubleValue)gbt.Results["Loss (test)"].Value).Value, 1E-6);
}
protected GradientBoostedTreesAlgorithm(GradientBoostedTreesAlgorithm original, Cloner cloner)
: base(original, cloner)
{
}
public void GradientBoostingTestTowerRelativeError() {
var gbt = new GradientBoostedTreesAlgorithm();
var provider = new HeuristicLab.Problems.Instances.DataAnalysis.RegressionRealWorldInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name.Contains("Tower"));
var regProblem = new RegressionProblem();
regProblem.Load(provider.LoadData(instance));
#region Algorithm Configuration
gbt.Problem = regProblem;
gbt.Seed = 0;
gbt.SetSeedRandomly = false;
gbt.Iterations = 3000;
gbt.MaxSize = 20;
gbt.Nu = 0.005;
gbt.LossFunctionParameter.Value = gbt.LossFunctionParameter.ValidValues.First(l => l.ToString().Contains("Relative"));
gbt.CreateSolution = false;
#endregion
RunAlgorithm(gbt);
Console.WriteLine(gbt.ExecutionTime);
Assert.AreEqual(0.061954221604374943, ((DoubleValue)gbt.Results["Loss (train)"].Value).Value, 1E-6);
Assert.AreEqual(0.06316303473499961, ((DoubleValue)gbt.Results["Loss (test)"].Value).Value, 1E-6);
}
public void GradientBoostingTestTowerSquaredError() {
var gbt = new GradientBoostedTreesAlgorithm();
var provider = new HeuristicLab.Problems.Instances.DataAnalysis.RegressionRealWorldInstanceProvider();
var instance = provider.GetDataDescriptors().Single(x => x.Name.Contains("Tower"));
var regProblem = new RegressionProblem();
regProblem.Load(provider.LoadData(instance));
#region Algorithm Configuration
gbt.Problem = regProblem;
gbt.Seed = 0;
gbt.SetSeedRandomly = false;
gbt.Iterations = 5000;
gbt.MaxSize = 20;
gbt.CreateSolution = false;
#endregion
RunAlgorithm(gbt);
Console.WriteLine(gbt.ExecutionTime);
Assert.AreEqual(267.68704241153921, ((DoubleValue)gbt.Results["Loss (train)"].Value).Value, 1E-6);
Assert.AreEqual(393.84704062205469, ((DoubleValue)gbt.Results["Loss (test)"].Value).Value, 1E-6);
}
protected GradientBoostedTreesAlgorithm(GradientBoostedTreesAlgorithm original, Cloner cloner)
: base(original, cloner) {
}
