public void TestOutcomesForSingleTypeSentence() {
var sentence = new[] {
"Elise",
"Wendel",
"appreciated",
"the",
"hint",
"and",
"enjoyed",
"a",
"delicious",
"traditional",
"meal",
"."
};
var nameSample = new NameSample(sentence, new[] {new Span(0, 2, "person")}, false);
var eventStream = new NameFinderEventStream(new CollectionObjectStream<NameSample>(nameSample));
Assert.AreEqual("person-" + NameFinderME.START, eventStream.Read().Outcome);
Assert.AreEqual("person-" + NameFinderME.Continue, eventStream.Read().Outcome);
for (int i = 0; i < 10; i++) {
Assert.AreEqual(NameFinderME.Other, eventStream.Read().Outcome);
}
Assert.Null(eventStream.Read());
}
public void TestOutcomesForSingleTypeSentence()
{
var sentence = new[] {
"Elise",
"Wendel",
"appreciated",
"the",
"hint",
"and",
"enjoyed",
"a",
"delicious",
"traditional",
"meal",
"."
};
var nameSample = new NameSample(sentence, new[] { new Span(0, 2, "person") }, false);
var eventStream = new NameFinderEventStream(new CollectionObjectStream <NameSample>(nameSample));
Assert.AreEqual("person-" + NameFinderME.START, eventStream.Read().Outcome);
Assert.AreEqual("person-" + NameFinderME.Continue, eventStream.Read().Outcome);
for (int i = 0; i < 10; i++)
{
Assert.AreEqual(NameFinderME.Other, eventStream.Read().Outcome);
}
Assert.Null(eventStream.Read());
}
/// <summary>
/// Trains a name finder model with the given parameters.
/// </summary>
/// <param name="languageCode">The language of the training data.</param>
/// <param name="type">Overrides the type parameter in the provided samples. This value can be null.</param>
/// <param name="samples">The training samples.</param>
/// <param name="parameters">The machine learning train parameters.</param>
/// <param name="factory">The name finder factory.</param>
/// <param name="monitor">
/// A evaluation monitor that can be used to listen the messages during the training or it can cancel the training operation.
/// This argument can be a <c>null</c> value.</param>
/// <returns>the newly <see cref="TokenNameFinderModel"/> trained model.</returns>
public static TokenNameFinderModel Train(string languageCode, string type, IObjectStream<NameSample> samples, TrainingParameters parameters, TokenNameFinderFactory factory, Monitor monitor) {
var beamSize = parameters.Get(Parameters.BeamSize, DefaultBeamSize);
var manifestInfoEntries = new Dictionary<string, string>();
var trainerType = TrainerFactory.GetTrainerType(parameters);
IMaxentModel meModel = null;
ML.Model.ISequenceClassificationModel<string> seqModel = null;
switch (trainerType) {
case TrainerType.EventModelTrainer:
var eventStream = new NameFinderEventStream(samples, type, factory.CreateContextGenerator(),
factory.CreateSequenceCodec());
var nfTrainer = TrainerFactory.GetEventTrainer(parameters, manifestInfoEntries, monitor);
meModel = nfTrainer.Train(eventStream);
break;
case TrainerType.EventModelSequenceTrainer:
var sampleStream = new NameSampleSequenceStream(samples, factory.CreateContextGenerator());
var nsTrainer = TrainerFactory.GetEventModelSequenceTrainer(parameters, manifestInfoEntries, monitor);
meModel = nsTrainer.Train(sampleStream);
break;
case TrainerType.SequenceTrainer:
var sequenceStream = new NameSampleSequenceStream(samples, factory.CreateContextGenerator());
var sqTrainer = TrainerFactory.GetSequenceModelTrainer(parameters, manifestInfoEntries, monitor);
seqModel = sqTrainer.Train(sequenceStream);
break;
default:
throw new InvalidOperationException("Unexpected trainer type!");
}
if (seqModel != null) {
return new TokenNameFinderModel(
languageCode,
seqModel,
factory.FeatureGenerator,
factory.Resources,
manifestInfoEntries,
factory.SequenceCodec,
factory);
}
return new TokenNameFinderModel(
languageCode,
meModel,
beamSize,
factory.FeatureGenerator,
factory.Resources,
manifestInfoEntries,
factory.SequenceCodec,
factory);
}
