/// <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> scModel = 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);
scModel = sqTrainer.Train(sequenceStream);
break;
default:
throw new InvalidOperationException("Unexpected trainer type!");
}
if (scModel != null)
{
return(new TokenNameFinderModel(
languageCode,
scModel,
factory.FeatureGenerator,
factory.Resources,
manifestInfoEntries,
factory.SequenceCodec));
}
return(new TokenNameFinderModel(
languageCode,
meModel,
beamSize,
factory.FeatureGenerator,
factory.Resources,
manifestInfoEntries,
factory.SequenceCodec));
}
/// <summary>
/// Creates a new event array based on the outcomes predicted by the specified parameters for the specified sequence.
/// </summary>
/// <param name="sequence">The sequence to be evaluated.</param>
/// <param name="model">The model.</param>
/// <returns>The event array.</returns>
public Event[] UpdateContext(Sequence sequence, AbstractModel model)
{
var tagger =
new NameFinderME(
new TokenNameFinderModel("x-unspecified", model, new Dictionary <string, object>(), null));
var sentence = sequence.GetSource <NameSample>().Sentence;
var tags = seqCodec.Encode(tagger.Find(sentence), sentence.Length);
return(NameFinderEventStream.GenerateEvents(sentence, tags, pcg).ToArray());
}
