public WebClassifierResultSet(DocumentSetClasses _setClassCollection, experimentExecutionContext _context, IFVExtractorSettings _extractorSettings)
{
setClassCollection = _setClassCollection;
featureVectors = new WebSiteClassifierResult(_setClassCollection, _extractorSettings);
items.Add(INPUTSET_NAME, featureVectors);
List <IWebPostClassifier> classifiers = new List <IWebPostClassifier>();
for (int i = 0; i < _context.setup.classifiers.Count; i++)
{
classifiers.Add(_context.setup.classifiers[i]);
}
Thread.Sleep(100);
if (classifiers.Count < _context.setup.classifiers.Count)
{
aceLog.log("::: MULTITHREADING --- CLASSIFIERS COUNT MISTMATCHED --- AUTOCORRECTION APPLIED :::");
for (int i = classifiers.Count - 1; i < _context.setup.classifiers.Count; i++)
{
classifiers.Add(_context.setup.classifiers[i]);
}
}
foreach (var cs in classifiers)
{
items.Add(cs.name, new WebSiteClassifierResult(_setClassCollection, _extractorSettings));
}
}
public WebSiteClassifierResult(DocumentSetClasses _setClassCollection, IFVExtractorSettings _settings)
{
setClassCollection = _setClassCollection;
foreach (var pair in setClassCollection.GetClasses())
{
WebSiteResultForClass resUnit = new WebSiteResultForClass(_settings.featureVectors);
resUnit.classID = pair.classID;
this.Add(pair.classID, resUnit);
}
}
public kFoldValidationCase GetDiagnosticCase(DocumentSetClasses classes)
{
kFoldValidationCase valCase = new kFoldValidationCase();
valCase.name = "Diagnostic";
valCase.id = items.Count;
DeployCase(valCase);
foreach (IDocumentSetClass c in classes.GetClasses())
{
valCase.trainingCases[c.classID].AddRange(c.WebSiteSample);
valCase.evaluationCases[c.classID].AddRange(c.WebSiteSample);
}
return(valCase);
}
/// <summary>
/// Sets the execution context.
/// </summary>
/// <param name="_manager">The manager.</param>
/// <param name="_setup">The setup.</param>
/// <param name="_tools">The tools.</param>
/// <param name="_classes">The classes.</param>
/// <param name="sufix">The sufix.</param>
/// <param name="chunker">The chunker.</param>
/// <param name="_masterExtractor">The master extractor.</param>
/// <param name="_logger">The logger.</param>
public void SetExecutionContext(experimentManager _manager, experimentSetup _setup, classifierTools _tools, DocumentSetClasses _classes, String sufix, chunkComposerBasic chunker, semanticFVExtractor _masterExtractor, ILogBuilder _logger = null)
{
if (_logger == null)
{
_logger = new builderForLog();
aceLog.consoleControl.setAsOutput(_logger, _setup.name);
}
logger = _logger;
chunkComposer = chunker;
setup = _setup;
tools = _tools;
tools.context = this;
classes = _classes;
// masterConstructor = _masterExtractor.termTableConstructor;
masterExtractor = _setup.featureVectorExtractors_semantic.First();
masterConstructor = masterExtractor.termTableConstructor;
manager = _manager;
String expContextName = "exp_" + setup.name.add(sufix, "_");
folder = manager.folder.Add(expContextName, "Experiment " + setup.name, "Directory with all information on the experiment [" + setup.name + "]");
errorNotesFolder = folder.Add("errors", "Error logs", "Directory with error reports produced if an exception occours. Normally, if everything was ok this folder should have only two files inside: directory_readme.txt and empty: note.txt).");
errorNotes = new experimentNotes(errorNotesFolder, "Notes (logs) about critical and non-critical errors that happen during experiment execution. If everything was ok - this file should remain empty");
notes = new experimentNotes(folder, "Notes on experiment setup and execution log");
aceLog.consoleControl.setAsOutput(notes, "Notes");
notes.log("Experiment [" + expContextName + "] initiated");
notes.AppendLine("About: " + setup.description);
notes.AppendHorizontalLine();
notes.SaveNote();
notes.AppendHeading("Feature extraction models");
var lnsc = chunkComposer.DescribeSelf();
lnsc.ForEach(x => notes.AppendLine(x));
notes.AppendLine(" - ");
List <String> mdn = new List <string>();
foreach (var md in setup.models)
{
if (mdn.Contains(md.name))
{
md.name += "_" + mdn.Count.ToString();
}
else
{
mdn.Add(md.name);
}
}
foreach (var md in setup.models)
{
String prefix = md.name;
md.classes = classes;
md.BuildFeatureVectorDefinition();
var lns = md.DescribeSelf();
lns.ForEach(x => notes.AppendLine(x));
kFoldValidationCollection validationCases = classes.BuildValidationCases(prefix, setup.validationSetup.k, tools.DoDebug, logger, folder, setup.validationSetup.randomize);
validationCases.pipelineCollection = pipelineCollection;
validationCases.connectContext(this, md);
validationCollections.Add(md.name, validationCases);
//md.postClassifiers = setup.classifiers;
}
}
