public void RandomForestsCrossValidationTest_2()
{
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_dnsHttpTls_cap);
var applicationProtocolModelEvaluator = this.AppIdentService.CreateApplicationProtocolModels(this.L7Conversations, 10);
var featureVectors = applicationProtocolModelEvaluator.TrainingFeatureVectors.ToList();
var appIdentAcordSource = new AppIdentAcordSource();
appIdentAcordSource.Init(featureVectors);
Console.WriteLine($"Feature vectors: {featureVectors.Count}");
var featureSelection = new FeatureSelection(appIdentAcordSource.FeatureSelector);
featureSelection.ProcessFeatureSelection(appIdentAcordSource, 0.5);
foreach (var feature in featureSelection.FeatureSelector.SelectedFeatures)
{
Console.WriteLine($"{feature.Name}");
}
var rfcModel = this.AccordAppIdent.GetBestRandomForestsWithGridSearch(appIdentAcordSource, out var bestParameters, out var minError);
// get the cross validation results
var cvResults = this.AccordAppIdent.GetCrossValidationResultsOfRandomForestModel(appIdentAcordSource, bestParameters);
Console.WriteLine("### CV Results ###");
Console.WriteLine("\n### Training stats ###");
Console.WriteLine(">> model error mean: {0}\n>> model std: {1}", Math.Round(cvResults.Training.Mean, 6), Math.Round(cvResults.Training.StandardDeviation, 6));
Console.WriteLine("\n### Validation stats ###");
Console.WriteLine(">> model error mean: {0}\n>> model std: {1}", Math.Round(cvResults.Validation.Mean, 6), Math.Round(cvResults.Validation.StandardDeviation, 6));
var minErorr = cvResults.Validation.Values.Min();
var bestIndex = cvResults.Validation.Values.IndexOf(minErorr);
var classifier = cvResults.Models[bestIndex];
var validationDataSource = classifier.Tag as AccordAppIdent.ValidationDataSource;
var predictedValues = classifier.Model.Decide(validationDataSource.ValidationInputs);
var i = 0;
foreach (var label in appIdentAcordSource.Labels.Distinct())
{
var conf = new ConfusionMatrix(validationDataSource.ValidationOutputs, predictedValues, i++);
Console.WriteLine($"##########################");
Console.WriteLine($"Protocol: {label}");
Console.WriteLine($"TP: {conf.TruePositives}");
Console.WriteLine($"TN: {conf.TrueNegatives}");
Console.WriteLine($"FN: {conf.FalseNegatives}");
Console.WriteLine($"FP: {conf.FalsePositives}");
Console.WriteLine($"Accuracy: {conf.Accuracy}");
Console.WriteLine($"Precision: {conf.Precision}");
Console.WriteLine($"Specificity: {conf.Specificity}");
Console.WriteLine($"Sensitivity: {conf.Sensitivity}");
Console.WriteLine($"FScore: {conf.FScore}");
}
}
public FeatureSelector EliminateCorelatedFeatures(AppIdentAcordSource appIdentAcordSource, double trashold, AppIdentTestContext appIdentTestContext)
{
var featureSelection = new FeatureSelection();
featureSelection.ProcessFeatureSelection(appIdentAcordSource, trashold);
var featureSelector = appIdentAcordSource.FeatureSelector;
appIdentTestContext.Save(featureSelector);
return(featureSelector);
}
//[DotMemoryUnit(CollectAllocations = true)]
//[AssertTraffic(AllocatedSizeInBytes = 1024*1024)]
public void CorrelationMatrixTest_M2()
{
MainWindow window = null;
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_dnsHttpTls_cap);
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_learn1_cap);
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_refSkype_cap);
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_streamSkypeHttpTls_cap);
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_testM1_cap);
this.ProcessPcapFile(SnoopersPcaps.Default.app_identification_testM2_cap);
List <L7Conversation> testSet;
var applicationProtocolModelEvaluator = this.AppIdentService.CreateApplicationProtocolModels(this.L7Conversations, 0.9, out testSet);
var featureVectors = applicationProtocolModelEvaluator.TrainingFeatureVectors.ToList();
var appIdentAcordSource = new AppIdentAcordSource();
appIdentAcordSource.Init(featureVectors);
var featureSelection = new FeatureSelection(appIdentAcordSource.FeatureSelector);
var selection = featureSelection.ProcessFeatureSelection(appIdentAcordSource, 0.3);
var correlationMatrix = selection.Last();
// The dispatcher thread
var t = new Thread(() =>
{
window = new MainWindow
{
DataContext = new MainViewModel(appIdentAcordSource.FeatureNames, correlationMatrix)
};
//window.DataContext = new MainViewModel();
// Initiates the dispatcher thread shutdown when the window closes
window.Closed += (s, e) => window.Dispatcher.InvokeShutdown();
window.Show();
// Makes the thread support message pumping
Dispatcher.Run();
});
// Configure the thread
t.SetApartmentState(ApartmentState.STA);
t.Start();
t.Join();
}