public static POSModel TrainModel(string path, ModelType mt)
        {
            FileStream          fs     = new FileStream(path, FileMode.Open, FileAccess.Read);
            WordTagSampleStream stream = new WordTagSampleStream(fs);

            TrainingParameters trainParams = new TrainingParameters();

            trainParams.Set(Parameters.Iterations, "100");
            trainParams.Set(Parameters.Cutoff, "0");
            switch (mt)
            {
            case ModelType.Maxent:
                trainParams.Set(Parameters.Algorithm, "MAXENT");
                break;

            case ModelType.Perceptron:
                trainParams.Set(Parameters.Algorithm, "PERCEPTRON");
                break;

            default:
                throw new NotSupportedException();
            }

            return(POSTaggerME.Train(TRAINING_LANGUAGE, stream, trainParams, new POSTaggerFactory()));
        }
Exemple #2
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        /// <summary>
        /// Trains a parser model with the given parameters.
        /// </summary>
        /// <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>
        /// <param name="languageCode">The language code.</param>
        /// <param name="samples">The data samples.</param>
        /// <param name="rules">The head rules.</param>
        /// <param name="parameters">The machine learnable parameters.</param>
        /// <returns>The trained <see cref="ParserModel" /> object.</returns>
        public static ParserModel Train(
            Monitor monitor,
            string languageCode,
            IObjectStream <Parse> samples,
            AbstractHeadRules rules,
            TrainingParameters parameters)
        {
            var dict = BuildDictionary(samples, rules, parameters);

            samples.Reset();

            var manifestInfoEntries = new Dictionary <string, string>();

            // build
            //System.err.println("Training builder");
            var bes            = new ParserEventStream(samples, rules, ParserEventTypeEnum.Build, dict);
            var buildReportMap = new Dictionary <string, string>();
            var buildTrainer   = TrainerFactory.GetEventTrainer(parameters.GetNamespace("build"), buildReportMap, monitor);


            var buildModel = buildTrainer.Train(bes);

            MergeReportIntoManifest(manifestInfoEntries, buildReportMap, "build");

            samples.Reset();

            // tag
            var posTaggerParams = parameters.GetNamespace("tagger");

            if (!posTaggerParams.Contains(Parameters.BeamSize))
            {
                posTaggerParams.Set(Parameters.BeamSize, "10");
            }


            var posModel = POSTaggerME.Train(languageCode, new PosSampleStream(samples),
                                             parameters.GetNamespace("tagger"), new POSTaggerFactory());

            samples.Reset();

            // chunk
            var chunkModel = ChunkerME.Train(languageCode,
                                             new ChunkSampleStream(samples),
                                             parameters.GetNamespace("chunker"),
                                             new ParserChunkerFactory());

            samples.Reset();

            // check
            //System.err.println("Training checker");
            var kes            = new ParserEventStream(samples, rules, ParserEventTypeEnum.Check);
            var checkReportMap = new Dictionary <string, string>();
            var checkTrainer   = TrainerFactory.GetEventTrainer(parameters.GetNamespace("check"), checkReportMap, monitor);

            var checkModel = checkTrainer.Train(kes);

            MergeReportIntoManifest(manifestInfoEntries, checkReportMap, "check");

            return(new ParserModel(languageCode, buildModel, checkModel, posModel, chunkModel, rules, manifestInfoEntries));
        }
Exemple #3
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        internal static POSModel TrainPosModel(ModelType type = ModelType.Maxent)
        {
            var p = new TrainingParameters();

            switch (type)
            {
            case ModelType.Maxent:
                p.Set(Parameters.Algorithm, "MAXENT");
                break;

            case ModelType.Perceptron:
                p.Set(Parameters.Algorithm, "PERCEPTRON");
                break;

            default:
                throw new NotSupportedException();
            }

            p.Set(Parameters.Iterations, "100");
            p.Set(Parameters.Cutoff, "5");

            return(POSTaggerME.Train("en", CreateSampleStream(), p, new POSTaggerFactory()));
        }
Exemple #4
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        /// <summary>
        /// Trains a parser model with the given parameters.
        /// </summary>
        /// <param name="languageCode">The language code.</param>
        /// <param name="samples">The data samples.</param>
        /// <param name="rules">The head rules.</param>
        /// <param name="parameters">The machine learnable parameters.</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="ParserModel"/> object.</returns>
        /// <exception cref="System.NotSupportedException">Trainer type is not supported.</exception>
        public static ParserModel Train(
            string languageCode,
            IObjectStream <Parse> samples,
            AbstractHeadRules rules,
            TrainingParameters parameters,
            Monitor monitor)
        {
            var manifestInfoEntries = new Dictionary <string, string>();

            System.Diagnostics.Debug.Print("Building dictionary");

            var dictionary = BuildDictionary(samples, rules, parameters);

            samples.Reset();

            // tag
            var posModel = POSTaggerME.Train(
                languageCode,
                new PosSampleStream(samples),
                parameters.GetNamespace("tagger"),
                new POSTaggerFactory(), monitor);

            samples.Reset();

            // chunk
            var chunkModel = ChunkerME.Train(
                languageCode,
                new ChunkSampleStream(samples),
                parameters.GetNamespace("chunker"),
                new ChunkerFactory(), monitor);

            samples.Reset();

            // build
            System.Diagnostics.Debug.Print("Training builder");
            var bes            = new ParserEventStream(samples, rules, ParserEventTypeEnum.Build, dictionary);
            var buildReportMap = new Dictionary <string, string>();
            var buildTrainer   = TrainerFactory.GetEventTrainer(parameters.GetNamespace("build"), buildReportMap, monitor);

            var buildModel = buildTrainer.Train(bes);

            Chunking.Parser.MergeReportIntoManifest(manifestInfoEntries, buildReportMap, "build");

            samples.Reset();

            // check
            System.Diagnostics.Debug.Print("Training checker");
            var kes            = new ParserEventStream(samples, rules, ParserEventTypeEnum.Check);
            var checkReportMap = new Dictionary <string, string>();

            var checkTrainer = TrainerFactory.GetEventTrainer(parameters.GetNamespace("check"), checkReportMap, monitor);

            var checkModel = checkTrainer.Train(kes);

            Chunking.Parser.MergeReportIntoManifest(manifestInfoEntries, checkReportMap, "check");

            samples.Reset();

            // attach
            System.Diagnostics.Debug.Print("Training attacher");
            var attachEvents    = new ParserEventStream(samples, rules, ParserEventTypeEnum.Attach);
            var attachReportMap = new Dictionary <string, string>();

            var attachTrainer = TrainerFactory.GetEventTrainer(parameters.GetNamespace("attach"), attachReportMap, monitor);

            var attachModel = attachTrainer.Train(attachEvents);

            Chunking.Parser.MergeReportIntoManifest(manifestInfoEntries, attachReportMap, "attach");

            return(new ParserModel(
                       languageCode,
                       buildModel,
                       checkModel,
                       attachModel,
                       posModel,
                       chunkModel,
                       rules,
                       ParserType.TreeInsert,
                       manifestInfoEntries));
        }