Examples of Train()

Examples of cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood.train()

94
95
96
97
98
99
100
101
102
103
104
      }
      else {
        CRFTrainerByThreadedLabelLikelihood trainer = new CRFTrainerByThreadedLabelLikelihood(crf,numThreads);
        trainer.setAddNoFactors(true);
        trainer.setGaussianPriorVariance(gpv);
        trainer.train(trainingSet,supIterations);
        trainer.shutdown();
      }
      runEvaluators();
    }
   
View Full Code Here

Examples of cc.mallet.fst.MEMMTrainer.train()

126
127
128
129
130
131
132
133
134
135
136
    MEMM memm = new MEMM (pipe2, null);
    memm.addFullyConnectedStatesForLabels ();
    MEMMTrainer memmt = new MEMMTrainer (memm);
    TransducerEvaluator memmeval = new TokenAccuracyEvaluator (new InstanceList[] {training2, testing2}, new String[] {"Training2", "Testing2"});
    memmt.train (training2, 5);
    memmeval.evaluate(memmt);

    CRFExtractor extor2 = hackCrfExtor (memm);
    Extraction e2 = extor2.extract (new ArrayIterator (data1));
View Full Code Here

Examples of cc.mallet.fst.MEMMTrainer.train()

122
123
124
125
126
127
128
129
130
131
132
    memm.addStartState();
    memm.setWeightsDimensionAsIn(training);
   
    MEMMTrainer memmt = new MEMMTrainer (memm);
//    memm.gatherTrainingSets (training); // ANNOYING: Need to set up per-instance training sets
    memmt.train (training, 1);  // Set weights dimension, gathers training sets, etc.

//    memm.print();
//    memm.printGradient = true;
//    memm.printInstanceLists();
View Full Code Here

Examples of cc.mallet.fst.MEMMTrainer.train()

145
146
147
148
149
150
151
152
153
154
155
    MEMM memm = new MEMM (p, null);
    memm.addFullyConnectedStatesForLabels ();
    memm.addStartState();
    memm.setWeightsDimensionAsIn(training);
    MEMMTrainer memmt = new MEMMTrainer (memm);
    memmt.train (training, 10);

    MEMM memm2 = (MEMM) TestSerializable.cloneViaSerialization (memm);

    Optimizable.ByGradientValue mcrf1 = memmt.getOptimizableMEMM(training);
    double val1 = mcrf1.getValue ();
View Full Code Here

Examples of cc.mallet.fst.MEMMTrainer.train()

377
378
379
380
381
382
383
384
385
386
387
      TestOptimizable.testValueAndGradient(minable);
    } else {
      System.out.println("Training Accuracy before training = " + memm.averageTokenAccuracy(lists[0]));
      System.out.println("Testing  Accuracy before training = " + memm.averageTokenAccuracy(lists[1]));
      System.out.println("Training...");
      memmt.train(lists[0], 1);
      System.out.println("Training Accuracy after training = " + memm.averageTokenAccuracy(lists[0]));
      System.out.println("Testing  Accuracy after training = " + memm.averageTokenAccuracy(lists[1]));
      System.out.println("Training results:");
      for (int i = 0; i < lists[0].size(); i++) {
        Instance inst = lists[0].get(i);
View Full Code Here

Examples of cc.mallet.fst.MEMMTrainer.train()

426
427
428
429
430
431
432
433
434
435
436
    } else {
      System.out.println("Training Accuracy before training = " + crf.averageTokenAccuracy(lists[0]));
      System.out.println("Testing  Accuracy before training = " + crf.averageTokenAccuracy(lists[1]));
      savedCRF = crf;
      System.out.println("Training serialized crf.");
      memmt.train(lists[0], 100);
      double preTrainAcc = crf.averageTokenAccuracy(lists[0]);
      double preTestAcc = crf.averageTokenAccuracy(lists[1]);
      System.out.println("Training Accuracy after training = " + preTrainAcc);
      System.out.println("Testing  Accuracy after training = " + preTestAcc);
      try {
View Full Code Here

Examples of cc.mallet.fst.semi_supervised.CRFTrainerByGE.train()

226
227
228
229
230
231
232
233
234
235
236
   
    CRFTrainerByGE trainer = new CRFTrainerByGE(crf,constraints,numThreads.value);
    if (eval != null) trainer.addEvaluator(eval);
    trainer.setGaussianPriorVariance(var);
    trainer.setNumResets(resets);
    trainer.train(training,iterations);

    return crf;
  }
 
  /**
 
View Full Code Here

Examples of cc.mallet.fst.semi_supervised.pr.CRFTrainerByPR.train()

257
258
259
260
261
262
263
264
265
266
267
    assert(numThreads.value > 0);
   
    CRFTrainerByPR trainer = new CRFTrainerByPR(crf,constraints,numThreads.value);
    trainer.addEvaluator(eval);
    trainer.setPGaussianPriorVariance(var);
    trainer.train(training,iterations,iterations);

    return crf;
  }
 
  public static CRF getCRF(InstanceList training, int[] orders, String defaultLabel, String forbidden, String allowed, boolean connected) {
View Full Code Here

Examples of cc.mallet.grmm.learning.ACRFTrainer.train()

57
58
59
60
61
62
63
64
65
66
67
    };

    ACRF acrf = new ACRF (pipe, tmpls);

    ACRFTrainer trainer = new DefaultAcrfTrainer ();
    trainer.train (acrf, training, null, testing, 99999);

    FileUtils.writeGzippedObject (crfFile, acrf);
  }
}
View Full Code Here

Examples of cc.mallet.grmm.learning.DefaultAcrfTrainer.train()

57
58
59
60
61
62
63
64
65
66
67
    };

    ACRF acrf = new ACRF (pipe, tmpls);

    ACRFTrainer trainer = new DefaultAcrfTrainer ();
    trainer.train (acrf, training, null, testing, 99999);

    FileUtils.writeGzippedObject (crfFile, acrf);
  }
}
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.