crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState("O").setInitialWeight(0.0);
crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState("O").setInitialWeight(0.0);
private static void configure(CRF _crf, InstanceList trainingSet) { // crf.addStatesForLabelsConnectedAsIn(trainingSet); // CRFTrainerByLabelLikelihood trainer = new // CRFTrainerByLabelLikelihood( // crf); // trainer.setGaussianPriorVariance(1d); int[] orders = new int[] { 1 }; Pattern forbiddenPat = Pattern.compile("\\s"); Pattern allowedPat = Pattern.compile(".*"); String outside = Jcas2TokenSequence.TARGET_O; String startName = _crf.addOrderNStates(trainingSet, orders, null, outside, forbiddenPat, allowedPat, true); // String startName = crf.addOrderNStates(trainingSet, orders, null, // null, null, null, true); for (int i = 0; i < _crf.numStates(); i++) _crf.getState(i).setInitialWeight(Transducer.IMPOSSIBLE_WEIGHT); _crf.getState(startName).setInitialWeight(0.0); }
Transducer.State s = crf.getState (i); if (s.getName().charAt(0) == 'I') s.setInitialWeight (Double.POSITIVE_INFINITY);
connected); for (int i = 0; i < crf.numStates(); i++) crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState(startName).setInitialWeight(0.0);
connected); for (int i = 0; i < crf.numStates(); i++) crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState(startName).setInitialWeight(0.0);
connected); for (int i = 0; i < crf.numStates(); i++) crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState(startName).setInitialWeight(0.0);
crf.getState(0).setInitialWeight(1.0); crf.getState(1).setInitialWeight(Transducer.IMPOSSIBLE_WEIGHT); crf.getState(0).setFinalWeight(0.0); crf.getState(1).setFinalWeight(0.0);
crf.getState(0).setInitialWeight(1.0); crf.getState(1).setInitialWeight(Transducer.IMPOSSIBLE_WEIGHT); crf.getState(0).setFinalWeight(0.0); crf.getState(1).setFinalWeight(0.0);
crf.getState(0).setInitialWeight(1.0); crf.getState(1).setInitialWeight(Transducer.IMPOSSIBLE_WEIGHT); crf.getState(0).setFinalWeight(0.0); crf.getState(1).setFinalWeight(0.0);
emissionMultinomial[i] = emissionEstimator[i].estimate(); transitionMultinomial[i] = transitionEstimator[i].estimate(); getState(i).setInitialWeight( initialMultinomial.logProbability(getState(i).getName()));
emissionMultinomial[i] = emissionEstimator[i].estimate(); transitionMultinomial[i] = transitionEstimator[i].estimate(); getState(i).setInitialWeight( initialMultinomial.logProbability(getState(i).getName()));
emissionMultinomial[i] = emissionEstimator[i].estimate(); transitionMultinomial[i] = transitionEstimator[i].estimate(); getState(i).setInitialWeight( initialMultinomial.logProbability(getState(i).getName()));
crf.getState(0).setInitialWeight(1.0); crf.getState(1).setInitialWeight(Transducer.IMPOSSIBLE_WEIGHT); crf.getState(0).setFinalWeight(0.0); crf.getState(1).setFinalWeight(0.0);
public static CRF getCRF(InstanceList training, int[] orders, String defaultLabel, String forbidden, String allowed, boolean connected) { Pattern forbiddenPat = Pattern.compile(forbidden); Pattern allowedPat = Pattern.compile(allowed); CRF crf = new CRF(training.getPipe(), (Pipe)null); String startName = crf.addOrderNStates(training, orders, null, defaultLabel, forbiddenPat, allowedPat, connected); for (int i = 0; i < crf.numStates(); i++) crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState(startName).setInitialWeight(0.0); crf.setWeightsDimensionDensely(); return crf; }
public void setAsStartState (State state) { for (int i = 0; i < numStates(); i++) { Transducer.State other = getState (i); if (other == state) { other.setInitialWeight (0); } else { other.setInitialWeight (IMPOSSIBLE_WEIGHT); } } weightsValueChanged(); }
public void setAsStartState (State state) { for (int i = 0; i < numStates(); i++) { Transducer.State other = getState (i); if (other == state) { other.setInitialWeight (0); } else { other.setInitialWeight (IMPOSSIBLE_WEIGHT); } } weightsValueChanged(); }
public static CRF getCRF(InstanceList training, int[] orders, String defaultLabel, String forbidden, String allowed, boolean connected) { Pattern forbiddenPat = Pattern.compile(forbidden); Pattern allowedPat = Pattern.compile(allowed); CRF crf = new CRF(training.getPipe(), (Pipe)null); String startName = crf.addOrderNStates(training, orders, null, defaultLabel, forbiddenPat, allowedPat, connected); for (int i = 0; i < crf.numStates(); i++) crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState(startName).setInitialWeight(0.0); crf.setWeightsDimensionDensely(); return crf; }
public static CRF getCRF(InstanceList training, int[] orders, String defaultLabel, String forbidden, String allowed, boolean connected) { Pattern forbiddenPat = Pattern.compile(forbidden); Pattern allowedPat = Pattern.compile(allowed); CRF crf = new CRF(training.getPipe(), (Pipe)null); String startName = crf.addOrderNStates(training, orders, null, defaultLabel, forbiddenPat, allowedPat, connected); for (int i = 0; i < crf.numStates(); i++) crf.getState(i).setInitialWeight (Transducer.IMPOSSIBLE_WEIGHT); crf.getState(startName).setInitialWeight(0.0); crf.setWeightsDimensionDensely(); return crf; }
public void setAsStartState (State state) { for (int i = 0; i < numStates(); i++) { Transducer.State other = getState (i); if (other == state) { other.setInitialWeight (0); } else { other.setInitialWeight (IMPOSSIBLE_WEIGHT); } } weightsValueChanged(); }