private static void RandomForest(AppIdentService appIdentService, AppIdentDataSource appIdentDataSource, AppIdentTestContext context)
{
Console.WriteLine($"{DateTime.Now} Running feature elimination with trashold { context.FeatureSelectionTreshold}.");
var featureSelector = appIdentService.EliminateCorelatedFeatures(appIdentDataSource, context.FeatureSelectionTreshold, context);
GridSearchParameterCollection bestParameters;
if (!File.Exists(context.BestParametersFilePath))
{
Console.WriteLine($"{DateTime.Now} Looking for best parameters.");
bestParameters = appIdentService.RandomForestGetBestParameters(appIdentDataSource, featureSelector, context);
}
else
{
Console.WriteLine($"{DateTime.Now} Loading best parameters.");
context.Load <GridSearchParameterCollection>(context.BestParametersFilePath, out bestParameters);
}
Console.WriteLine($"{DateTime.Now} Running cross validation.");
var classificationStatisticsMeter =
appIdentService.RandomForestCrossValidation(appIdentDataSource, context.FeatureSelector, bestParameters, context.CrossValidationFolds, context);
Console.WriteLine($"{DateTime.Now} Cross validation results:");
classificationStatisticsMeter.PrintResults();
var model = context.Model;
Console.WriteLine($"{DateTime.Now} Running classification");
appIdentService.AccordClassify(appIdentDataSource, model, context.FeatureSelector, context);
Console.WriteLine($"{DateTime.Now} Classification results:");
classificationStatisticsMeter.PrintResults();
context.Save();
}
private static void Epi(AppIdentService appIdentService, AppIdentDataSource appIdentDataSource, AppIdentTestContext context)
{
Console.WriteLine($"{DateTime.Now} Running feature elimination with trashold { context.FeatureSelectionTreshold}.");
var featureSelector = appIdentService.EliminateCorelatedFeatures(appIdentDataSource, context.FeatureSelectionTreshold, context);
Console.WriteLine($"{DateTime.Now} Running classification");
var classificationStatisticsMeter = appIdentService.EpiClasify(appIdentDataSource, featureSelector, context);
Console.WriteLine($"{DateTime.Now} Classification results:");
classificationStatisticsMeter.PrintResults();
}
private static void Bayesian(AppIdentService appIdentService, AppIdentDataSource appIdentDataSource, AppIdentTestContext context)
{
Console.WriteLine($"{DateTime.Now} Running feature elimination with trashold { context.FeatureSelectionTreshold}.");
var featureSelector = appIdentService.EliminateCorelatedFeatures(appIdentDataSource, context.FeatureSelectionTreshold, context);
Console.WriteLine($"{DateTime.Now} Running classification.");
var classificationStatisticsMeter = appIdentService.BayesianClassify(appIdentDataSource, context.TrainingToVerificationRation, 0.99, context);
Console.WriteLine($"{DateTime.Now} Classification results:");
classificationStatisticsMeter.PrintResults();
context.Save();
}
static void Main(string[] args)
{
var watch = new Stopwatch();
watch.Start();
var options = new Options();
if (!Parser.Default.ParseArguments(args, options))
{
DebuggerCheckExit();
return;
}
//options.TrainingToVerificationRation = 0.7;
//options.FeatureSelectionTrashold = 0.7;
//options.IsEpi = true;
//options.IsUseFullName = false;
//options.MinFlows = 17;
if (!options.IsEpi && !options.IsRandomForest && !options.IsBayesian)
{
Console.WriteLine("No classification method selected.");
DebuggerCheckExit();
return;
}
var context = new AppIdentTestContext("cli", DateTime.Now)
{
MinFlows = options.MinFlows,
TrainingToVerificationRation = options.TrainingToVerificationRation,
FeatureSelectionTreshold = options.FeatureSelectionTrashold,
CrossValidationFolds = options.CrossValidationFolds,
IsEpi = options.IsEpi,
IsRandomForest = options.IsRandomForest,
IsBayesian = options.IsBayesian,
IsUseFullName = options.IsUseFullName,
BestParametersFilePath = options.BestParametersFilePath,
};
context.ChangeNameByParameters();
context.Save();
SetLabelType(options);
Console.WriteLine($"{DateTime.Now} Loading: {options.AppIdentDataSource}");
var appIdentDataSource = context.LoadAppIdentDataSource(options.AppIdentDataSource);
Console.WriteLine($"{DateTime.Now} Repartitioning ratio {context.TrainingToVerificationRation} with min flows {context.MinFlows}");
appIdentDataSource.RepartitionFeatureVectorsTestingAndVerificationDatasets(context.TrainingToVerificationRation, context.MinFlows);
context.SavePartitioning(appIdentDataSource);
context.AppIdentDataSource = appIdentDataSource;
if (!appIdentDataSource.TrainingSet.Any() || !appIdentDataSource.VerificationSet.Any())
{
Console.WriteLine("No testing or verification data present after partitioning and filtering by minflow.");
DebuggerCheckExit();
return;
}
var appIdentService = new AppIdentService();
if (options.IsRandomForest)
{
RandomForest(appIdentService, appIdentDataSource, context);
}
if (options.IsEpi)
{
Epi(appIdentService, appIdentDataSource, context);
}
if (options.IsBayesian)
{
Bayesian(appIdentService, appIdentDataSource, context);
}
watch.Stop();
context.RunningTime = watch.Elapsed;
context.Save();
Console.WriteLine($"{DateTime.Now} Running time: {watch.Elapsed}");
DebuggerCheckExit();
}
public AccordAppIdent(AppIdentService appIdentService)
{
this.AppIdentService = appIdentService;
}
