private static void Main()
{
var features = new List <Feature <Comment> >();
var badWordFeature = new BadWordFeature();
features.Add(new Feature <Comment>("Bad word",
comment => badWordFeature.NumberOfBadWords(comment), 1d));
features.Add(new Feature <Comment>("Reputation",
comment => Math.Log(1d + comment.UserReputation), -1d));
features.AddRange(BadWordFeature.ContainsIndividualWords());
IList <Comment> comments = new CommentRepository().GetComments();
IList <Sample <Comment> > samples =
comments.Select(
comment =>
ConvertToSample(comment, features)).
ToList();
var logisticRegression = new LogisticRegression <Comment>(UseSecondOrder);
var stopwatch = new Stopwatch();
stopwatch.Start();
IList <Dimension <Comment> > dimensions = logisticRegression.Iterate(samples,
features, 0.01d);
stopwatch.Stop();
Console.WriteLine("Duration: {0:N4} seconds", stopwatch.Elapsed.TotalSeconds);
// Testing some different reputations:
for (int userReputation = 0; userReputation < 10; userReputation++)
{
var test = new Sample <Comment>(
new Comment
{
Text = "Hej med dig. Sex?",
UserReputation = userReputation
},
"X", false, features, UseSecondOrder);
Vector <double> denseVector =
new DenseVector(dimensions.Select(x => x.Theta).ToArray());
double probability = test.GetProbability(denseVector);
Console.WriteLine("{0}, {1:P2}", userReputation, probability);
}
Console.ReadKey();
}
