/// <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 POSTaggerME(new POSModel("x-unspecified", model, null, new POSTaggerFactory())); var sample = sequence.GetSource <POSSample>(); var tags = tagger.Tag(sample.Sentence); return(POSSampleEventStream.GenerateEvents( sample.Sentence, tags, Array.ConvertAll(sample.AdditionalContext, input => (object)input), contextGenerator).ToArray()); }
/// <summary> /// Trains a Part of Speech model with the given parameters. /// </summary> /// <param name="languageCode">The language code.</param> /// <param name="samples">The data samples.</param> /// <param name="parameters">The machine learnable parameters.</param> /// <param name="factory">The sentence detector 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 trained <see cref="POSModel"/> object.</returns> /// <exception cref="System.NotSupportedException">Trainer type is not supported.</exception> public static POSModel Train(string languageCode, IObjectStream <POSSample> samples, TrainingParameters parameters, POSTaggerFactory factory, Monitor monitor) { //int beamSize = trainParams.Get(Parameters.BeamSize, NameFinderME.DefaultBeamSize); var contextGenerator = factory.GetPOSContextGenerator(); var manifestInfoEntries = new Dictionary <string, string>(); var trainerType = TrainerFactory.GetTrainerType(parameters); IMaxentModel posModel = null; ML.Model.ISequenceClassificationModel <string> seqPosModel = null; switch (trainerType) { case TrainerType.EventModelTrainer: var es = new POSSampleEventStream(samples, contextGenerator); var trainer = TrainerFactory.GetEventTrainer(parameters, manifestInfoEntries, monitor); posModel = trainer.Train(es); break; case TrainerType.EventModelSequenceTrainer: var ss = new POSSampleSequenceStream(samples, contextGenerator); var trainer2 = TrainerFactory.GetEventModelSequenceTrainer(parameters, manifestInfoEntries, monitor); posModel = trainer2.Train(ss); break; case TrainerType.SequenceTrainer: var trainer3 = TrainerFactory.GetSequenceModelTrainer(parameters, manifestInfoEntries, monitor); // TODO: This will probably cause issue, since the feature generator uses the outcomes array var ss2 = new POSSampleSequenceStream(samples, contextGenerator); seqPosModel = trainer3.Train(ss2); break; default: throw new NotSupportedException("Trainer type is not supported."); } if (posModel != null) { return(new POSModel(languageCode, posModel, manifestInfoEntries, factory)); } return(new POSModel(languageCode, seqPosModel, manifestInfoEntries, factory)); }