public void SupportVectorMachinePerformanceTest() {
ex = null;
var cv = new CrossValidation();
cv.Algorithm = new SupportVectorRegression();
var rand = new HeuristicLab.Random.MersenneTwister();
double[,] data = GenerateData(1000, rand);
List<string> variables = new List<string>() { "x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9", "x10", "y" };
Dataset ds = new Dataset(variables, data);
cv.Problem.ProblemDataParameter.ActualValue = new RegressionProblemData(ds, variables.Take(10), variables.Last());
cv.Folds.Value = 5;
cv.SamplesStart.Value = 0;
cv.SamplesEnd.Value = 999;
cv.ExceptionOccurred += new EventHandler<EventArgs<Exception>>(cv_ExceptionOccurred);
cv.Stopped += new EventHandler(cv_Stopped);
cv.Prepare();
cv.Start();
trigger.WaitOne();
if (ex != null) throw ex;
TestContext.WriteLine("Runtime: {0}", cv.ExecutionTime.ToString());
}
public void SupportVectorMachinePerformanceTest()
{
ex = null;
var cv = new CrossValidation();
cv.Algorithm = new SupportVectorRegression();
var rand = new HeuristicLab.Random.MersenneTwister();
double[,] data = GenerateData(1000, rand);
List <string> variables = new List <string>()
{
"x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9", "x10", "y"
};
Dataset ds = new Dataset(variables, data);
cv.Problem.ProblemDataParameter.ActualValue = new RegressionProblemData(ds, variables.Take(10), variables.Last());
cv.Folds.Value = 5;
cv.SamplesStart.Value = 0;
cv.SamplesEnd.Value = 999;
cv.ExceptionOccurred += new EventHandler <EventArgs <Exception> >(cv_ExceptionOccurred);
cv.Prepare();
cv.Start();
if (ex != null)
{
throw ex;
}
TestContext.WriteLine("Runtime: {0}", cv.ExecutionTime.ToString());
}