public void ClassifyTest()
{
var classifier = new NaiveBayesClassifier();
var trainingData = new List <Tuple <string, IEnumerable <string> > >
{
new Tuple <string, IEnumerable <string> >("Food", new[] { "apple", "orange" }),
new Tuple <string, IEnumerable <string> >("Food", new[] { "apple", "cake", "banana" }),
new Tuple <string, IEnumerable <string> >("Animal", new[] { "cat", "dog" }),
new Tuple <string, IEnumerable <string> >("Animal", new[] { "bird", "cat", "apple" }),
};
classifier.Train(trainingData);
var category = classifier.Classify(new[] { "dog" });
Assert.AreEqual("Animal", category);
category = classifier.Classify(new[] { "apple", "banana" });
Assert.AreEqual("Food", category);
}
public override void Train(ILabeledExampleCollection <LblT, SparseVector <double> > dataset)
{
var ds = (LabeledDataset <LblT, SparseVector <double> >)dataset;
mModel.Train((LabeledDataset <LblT, BinaryVector>)ds.ConvertDataset(typeof(BinaryVector), false));
}