Package cc.mallet.fst

Examples of cc.mallet.fst.TokenAccuracyEvaluator

107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
    testing.addThruPipe (new ArrayIterator (data1));

    CRF crf = new CRF (pipe, null);
    crf.addFullyConnectedStatesForLabels ();
    CRFTrainerByLabelLikelihood crft = new CRFTrainerByLabelLikelihood (crf);
    TokenAccuracyEvaluator eval = new TokenAccuracyEvaluator (new InstanceList[] {training, testing}, new String[] {"Training", "Testing"});
    for (int i = 0; i < 5; i++) {
      crft.train (training, 1);
      eval.evaluate(crft);
    }

    CRFExtractor extor = hackCrfExtor (crf);
    Extraction e1 = extor.extract (new ArrayIterator (data1));

    Pipe pipe2 = TestMEMM.makeSpacePredictionPipe ();
    InstanceList training2 = new InstanceList (pipe2);
    training2.addThruPipe (new ArrayIterator (data0));
    InstanceList testing2 = new InstanceList (pipe2);
    testing2.addThruPipe (new ArrayIterator (data1));

    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));

    if (!htmlDir.exists ()) htmlDir.mkdir ();
View Full Code Here
464
465
466
467
468
469
470
471
472
473
474
   
   
    if (testOption.value != null)
    {
      if (testOption.value.startsWith("lab"))
        eval = new TokenAccuracyEvaluator(new InstanceList[] {trainingData, testData}, new String[] {"Training", "Testing"});
      else if (testOption.value.startsWith("seg="))
      {
        String[] pairs = testOption.value.substring(4).split(",");
        if (pairs.length < 1)
        {
View Full Code Here
860
861
862
863
864
865
866
867
868
869
870
871
    CRFTrainerByLabelLikelihood crft = new CRFTrainerByLabelLikelihood(crf);
    crft.setUseSparseWeights(true);

    crft.trainIncremental(lists[0]);

    TokenAccuracyEvaluator eval = new TokenAccuracyEvaluator(lists,
        new String[] { "Train", "Test" });
    eval.evaluateInstanceList(crft, lists[1], "Test");

    assertEquals(0.9409, eval.getAccuracy("Test"), 0.001);

  }
View Full Code Here
TOP

Related Classes of cc.mallet.fst.TokenAccuracyEvaluator

  • cc.mallet.extract.test.TestLatticeViewer
  • cc.mallet.fst.semi_supervised.tui.SimpleTaggerWithConstraints
  • cc.mallet.fst.tests.TestCRF
  • cc.mallet.types.Instance
  • cc.mallet.types.Sequence
    • Copyright © 2018 www.massapicom. 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.