public void TestSimpleTraining()
{
IObjectStream <DocumentSample> samples = new GenericObjectStream <DocumentSample>(
new DocumentSample("1", new[] { "a", "b", "c", "1", "2" }),
new DocumentSample("1", new[] { "a", "b", "c", "3", "4" }),
new DocumentSample("0", new[] { "x", "y", "z" }),
new DocumentSample("0", new[] { "x", "y", "z", "5", "6" }),
new DocumentSample("0", new[] { "x", "y", "z", "7", "8" }));
var param = new TrainingParameters();
param.Set(Parameters.Iterations, "100");
param.Set(Parameters.Cutoff, "0");
param.Set(Parameters.Algorithm, Parameters.Algorithms.NaiveBayes);
var model = DocumentCategorizerME.Train("x-unspecified", samples, param, new DocumentCategorizerFactory(WhitespaceTokenizer.Instance, new [] { new BagOfWordsFeatureGenerator() }));
var doccat = new DocumentCategorizerME(model);
var aProbs = doccat.Categorize("a");
Assert.AreEqual("1", doccat.GetBestCategory(aProbs));
var bProbs = doccat.Categorize("x");
Assert.AreEqual("0", doccat.GetBestCategory(bProbs));
//test to make sure sorted map's last key is cat 1 because it has the highest score.
var sortedScoreMap = doccat.SortedScoreMap("a");
var last = sortedScoreMap.Last();
Assert.AreEqual("1", last.Value[0]);
}
public void testSimpleTraining() {
IObjectStream<DocumentSample> samples = new GenericObjectStream<DocumentSample>(new[] {
new DocumentSample("1", new[] {"a", "b", "c"}),
new DocumentSample("1", new[] {"a", "b", "c", "1", "2"}),
new DocumentSample("1", new[] {"a", "b", "c", "3", "4"}),
new DocumentSample("0", new[] {"x", "y", "z"}),
new DocumentSample("0", new[] {"x", "y", "z", "5", "6"}),
new DocumentSample("0", new[] {"x", "y", "z", "7", "8"})
});
var param = new TrainingParameters();
param.Set(Parameters.Iterations, "100");
param.Set(Parameters.Cutoff, "0");
var model = DocumentCategorizerME.Train("x-unspecified", samples, param, new DocumentCategorizerFactory());
var doccat = new DocumentCategorizerME(model);
var aProbs = doccat.Categorize("a");
Assert.AreEqual("1", doccat.GetBestCategory(aProbs));
var bProbs = doccat.Categorize("x");
Assert.AreEqual("0", doccat.GetBestCategory(bProbs));
//test to make sure sorted map's last key is cat 1 because it has the highest score.
var sortedScoreMap = doccat.SortedScoreMap("a");
foreach (var pair in sortedScoreMap) {
Assert.AreEqual("1", pair.Value[0]);
break;
}
}
public void TestSimpleTraining()
{
IObjectStream <DocumentSample> samples = new GenericObjectStream <DocumentSample>(new[] {
new DocumentSample("1", new[] { "a", "b", "c" }),
new DocumentSample("1", new[] { "a", "b", "c", "1", "2" }),
new DocumentSample("1", new[] { "a", "b", "c", "3", "4" }),
new DocumentSample("0", new[] { "x", "y", "z" }),
new DocumentSample("0", new[] { "x", "y", "z", "5", "6" }),
new DocumentSample("0", new[] { "x", "y", "z", "7", "8" })
});
var param = new TrainingParameters();
param.Set(Parameters.Iterations, "100");
param.Set(Parameters.Cutoff, "0");
var model = DocumentCategorizerME.Train("x-unspecified", samples, param, new DocumentCategorizerFactory());
var doccat = new DocumentCategorizerME(model);
var aProbs = doccat.Categorize("a");
Assert.AreEqual("1", doccat.GetBestCategory(aProbs));
var bProbs = doccat.Categorize("x");
Assert.AreEqual("0", doccat.GetBestCategory(bProbs));
//test to make sure sorted map's last key is cat 1 because it has the highest score.
var sortedScoreMap = doccat.SortedScoreMap("a");
// first 0
// second 1 (last)
foreach (var pair in sortedScoreMap)
{
Assert.AreEqual("0", pair.Value[0]);
break;
}
}