public void TestUsers()
{
var userParser = new Parser();
userParser.BuildUsers(UsersXml);
Assert.That(userParser.Users[12], Is.EqualTo("Sam Neff"));
}
public void TestCaseText()
{
var samCases = @"../../../Assets/Fogbugz/sam.xml";
var userParser = new Parser();
var cases = userParser.GetCases(UsersXml, samCases);
}
public void TestParser(string path)
{
var parser = new Parser();
var cases = parser.GetCases(UsersXml, path);
Func<Case, Document> caseTransform =
i =>
i.ToDoc(@case => @case.Area,
@case => @case.Title);
#region Event Text comment
//@case.Events.Aggregate("", (acc, bug) => acc + " " + Regex.Replace(bug.Text, Regex.Escape("[") + "code" + Regex.Escape("]") + ".*" + Regex.Escape("[") + "/code" + Regex.Escape("]"), "")));
#endregion
var total = cases.Count();
var trainingSet = cases.Take((int)(total * (3.0 / 4))).Select(caseTransform).ToList();
var validationSet = cases.Skip((int)(total * (3.0 / 4))).Select(caseTransform).ToList();
var trainedData = NaiveBayes.TrainBayes(trainingSet);
var successRate = 0.0;
foreach (var @case in validationSet)
{
if (NaiveBayes.Classify(@case, trainedData).Name == @case.Class.Name)
{
successRate++;
}
}
successRate = successRate/validationSet.Count();
foreach (var type in trainedData.Probabilities)
{
Console.WriteLine(type.Class.Name);
Console.WriteLine("--------------------");
type.Top(10).ForEach(i => Console.WriteLine("[{1:0.00}] {0}", i.Word, i.Probability));
Console.WriteLine();
Console.WriteLine();
}
Console.WriteLine("Prediction success rate is {0:0.00}%", successRate * 100);
}
