Package opennlp.tools.ml

Examples of opennlp.tools.ml.EventTrainer.train()

333
334
335
336
337
338
339
340
341
342
343
    if (TrainerType.EVENT_MODEL_TRAINER.equals(trainerType)) {
      ObjectStream<Event> eventStream = new NameFinderEventStream(samples, type,
              factory.createContextGenerator(), factory.createSequenceCodec());

      EventTrainer trainer = TrainerFactory.getEventTrainer(trainParams.getSettings(), manifestInfoEntries);
      nameFinderModel = trainer.train(eventStream);
    } // TODO: Maybe it is not a good idea, that these two don't use the context generator ?!
    // These also don't use the sequence codec ?!
    else if (TrainerType.EVENT_MODEL_SEQUENCE_TRAINER.equals(trainerType)) {
      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, factory.createContextGenerator());
View Full Code Here
341
342
343
344
345
346
347
348
349
350
351
    else if (TrainerType.EVENT_MODEL_SEQUENCE_TRAINER.equals(trainerType)) {
      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, factory.createContextGenerator());

      EventModelSequenceTrainer trainer = TrainerFactory.getEventModelSequenceTrainer(
              trainParams.getSettings(), manifestInfoEntries);
      nameFinderModel = trainer.train(ss);
    } else if (TrainerType.SEQUENCE_TRAINER.equals(trainerType)) {
      SequenceTrainer trainer = TrainerFactory.getSequenceModelTrainer(
              trainParams.getSettings(), manifestInfoEntries);

      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, factory.createContextGenerator(), false);
View Full Code Here
347
348
349
350
351
352
353
354
355
356
357
    } else if (TrainerType.SEQUENCE_TRAINER.equals(trainerType)) {
      SequenceTrainer trainer = TrainerFactory.getSequenceModelTrainer(
              trainParams.getSettings(), manifestInfoEntries);

      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, factory.createContextGenerator(), false);
      seqModel = trainer.train(ss);
    } else {
      throw new IllegalStateException("Unexpected trainer type!");
    }

    if (seqModel != null) {
View Full Code Here
415
416
417
418
419
420
421
422
423
424
425
    if (TrainerType.EVENT_MODEL_TRAINER.equals(trainerType)) {
      ObjectStream<Event> eventStream = new NameFinderEventStream(samples, type,
              new DefaultNameContextGenerator(featureGenerator), new BioCodec());

      EventTrainer trainer = TrainerFactory.getEventTrainer(trainParams.getSettings(), manifestInfoEntries);
      nameFinderModel = trainer.train(eventStream);
    } else if (TrainerType.EVENT_MODEL_SEQUENCE_TRAINER.equals(trainerType)) {
      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, featureGenerator);

      EventModelSequenceTrainer trainer = TrainerFactory.getEventModelSequenceTrainer(
              trainParams.getSettings(), manifestInfoEntries);
View Full Code Here
421
422
423
424
425
426
427
428
429
430
431
    } else if (TrainerType.EVENT_MODEL_SEQUENCE_TRAINER.equals(trainerType)) {
      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, featureGenerator);

      EventModelSequenceTrainer trainer = TrainerFactory.getEventModelSequenceTrainer(
              trainParams.getSettings(), manifestInfoEntries);
      nameFinderModel = trainer.train(ss);
    } else if (TrainerType.SEQUENCE_TRAINER.equals(trainerType)) {
      SequenceTrainer trainer = TrainerFactory.getSequenceModelTrainer(
              trainParams.getSettings(), manifestInfoEntries);

      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, featureGenerator, false);
View Full Code Here
427
428
429
430
431
432
433
434
435
436
437
    } else if (TrainerType.SEQUENCE_TRAINER.equals(trainerType)) {
      SequenceTrainer trainer = TrainerFactory.getSequenceModelTrainer(
              trainParams.getSettings(), manifestInfoEntries);

      NameSampleSequenceStream ss = new NameSampleSequenceStream(samples, featureGenerator, false);
      seqModel = trainer.train(ss);
    } else {
      throw new IllegalStateException("Unexpected trainer type!");
    }

     // TODO: Pass the sequence codec down to the model! We will just store the class
View Full Code Here
290
291
292
293
294
295
296
297
298
299
300
    if (TrainerType.EVENT_MODEL_TRAINER.equals(trainerType)) {
      ObjectStream<Event> es = new POSSampleEventStream(samples, contextGenerator);

      EventTrainer trainer = TrainerFactory.getEventTrainer(trainParams.getSettings(),
          manifestInfoEntries);
      posModel = trainer.train(es);
    }
    else if (TrainerType.EVENT_MODEL_SEQUENCE_TRAINER.equals(trainerType)) {
      POSSampleSequenceStream ss = new POSSampleSequenceStream(samples, contextGenerator);
      EventModelSequenceTrainer trainer = TrainerFactory.getEventModelSequenceTrainer(trainParams.getSettings(),
          manifestInfoEntries);
View Full Code Here
296
297
298
299
300
301
302
303
304
305
306
    }
    else if (TrainerType.EVENT_MODEL_SEQUENCE_TRAINER.equals(trainerType)) {
      POSSampleSequenceStream ss = new POSSampleSequenceStream(samples, contextGenerator);
      EventModelSequenceTrainer trainer = TrainerFactory.getEventModelSequenceTrainer(trainParams.getSettings(),
          manifestInfoEntries);
      posModel = trainer.train(ss);
    }
    else if (TrainerType.SEQUENCE_TRAINER.equals(trainerType)) {
      SequenceTrainer trainer = TrainerFactory.getSequenceModelTrainer(
          trainParams.getSettings(), manifestInfoEntries);
View Full Code Here
305
306
307
308
309
310
311
312
313
314
315
          trainParams.getSettings(), manifestInfoEntries);

      // TODO: This will probably cause issue, since the feature generator uses the outcomes array

      POSSampleSequenceStream ss = new POSSampleSequenceStream(samples, contextGenerator);
      seqPosModel = trainer.train(ss);
    }
    else {
      throw new IllegalArgumentException("Trainer type is not supported: " + trainerType);
    }
View Full Code Here
214
215
216
217
218
219
220
221
222
223
224
    if (TrainerType.EVENT_MODEL_TRAINER.equals(trainerType)) {
      ObjectStream<Event> es = new ChunkerEventStream(in, factory.getContextGenerator());
      EventTrainer trainer = TrainerFactory.getEventTrainer(mlParams.getSettings(),
          manifestInfoEntries);
      chunkerModel = trainer.train(es);
    }
    else if (TrainerType.SEQUENCE_TRAINER.equals(trainerType)) {
      SequenceTrainer trainer = TrainerFactory.getSequenceModelTrainer(
          mlParams.getSettings(), manifestInfoEntries);
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.