Esempio n. 1
0
        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);
        }
Esempio n. 2
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        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));
        }