public void GaussianProcessRegressionPerformanceTest()
{
ex = null;
var alg = new GaussianProcessRegression();
alg.Engine = new HeuristicLab.SequentialEngine.SequentialEngine();
alg.SetSeedRandomly = false;
alg.Problem = new RegressionProblem();
var provider = new RegressionCSVInstanceProvider();
var problemData = (RegressionProblemData)provider.ImportData(@"Test Resources\co2.txt");
problemData.TargetVariableParameter.ActualValue = problemData.TargetVariableParameter.ValidValues.First(x => x.Value == "interpolated");
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "year"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "month"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "average"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "interpolated"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "trend"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "#days"), false);
alg.Problem.ProblemDataParameter.Value = problemData;
alg.ExceptionOccurred += new EventHandler <EventArgs <Exception> >(cv_ExceptionOccurred);
alg.Prepare();
alg.Start();
if (ex != null)
{
throw ex;
}
TestContext.WriteLine("Runtime: {0}", alg.ExecutionTime.ToString());
}
public void GaussianProcessRegressionPerformanceTest() {
ex = null;
var alg = new GaussianProcessRegression();
alg.Engine = new HeuristicLab.SequentialEngine.SequentialEngine();
alg.Problem = new RegressionProblem();
var provider = new RegressionCSVInstanceProvider();
var problemData = (RegressionProblemData)provider.ImportData(@"Test Resources\co2.txt");
problemData.TargetVariableParameter.ActualValue = problemData.TargetVariableParameter.ValidValues.First(x => x.Value == "interpolated");
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "year"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "month"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "average"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "interpolated"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "trend"), false);
problemData.InputVariables.SetItemCheckedState(problemData.InputVariables.First(x => x.Value == "#days"), false);
alg.Problem.ProblemDataParameter.Value = problemData;
alg.ExceptionOccurred += new EventHandler<EventArgs<Exception>>(cv_ExceptionOccurred);
alg.Stopped += new EventHandler(cv_Stopped);
alg.Prepare();
alg.Start();
trigger.WaitOne();
if (ex != null) throw ex;
TestContext.WriteLine("Runtime: {0}", alg.ExecutionTime.ToString());
}
private GaussianProcessRegression CreateGaussianProcessRegressionSample()
{
var gpr = new GaussianProcessRegression();
var provider = new VariousInstanceProvider();
var instance = provider.GetDataDescriptors().Where(x => x.Name.Contains("Spatial co-evolution")).Single();
var regProblem = new RegressionProblem();
regProblem.Load(provider.LoadData(instance));
#region Algorithm Configuration
gpr.Name = "Gaussian Process Regression";
gpr.Description = "A Gaussian process regression algorithm which solves the spatial co-evolution benchmark problem";
gpr.Problem = regProblem;
gpr.CovarianceFunction = new CovarianceSquaredExponentialIso();
gpr.MeanFunction = new MeanConst();
gpr.MinimizationIterations = 20;
gpr.Seed = 0;
gpr.SetSeedRandomly = true;
#endregion
gpr.Engine = new ParallelEngine.ParallelEngine();
return(gpr);
}
