edu.stanford.nlp.ie
Class SeminarsPrior<IN extends CoreMap>

java.lang.Object
  edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior<IN>
      edu.stanford.nlp.ie.SeminarsPrior<IN>

All Implemented Interfaces:

SequenceListener, SequenceModel

public class SeminarsPrior<IN extends CoreMap>
extends EntityCachingAbstractSequencePrior<IN>

Author:

Jenny Finkel

Field Summary

Fields inherited from class edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior

backgroundSymbol, classIndex, doc, numClasses, possibleValues, sequence

Constructor Summary

SeminarsPrior(java.lang.String backgroundSymbol, Index<java.lang.String> classIndex, java.util.List<IN> doc)

Method Summary

double

scoreOf(int[] sequence) Computes the score assigned by this model to the whole sequence.

Methods inherited from class edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior

addingSingletonEntity, appendingEntity, extractEntity, getConditionalDistribution, getNumClasses, getPossibleValues, joiningTwoEntities, leftWindow, length, matches, noChange, otherOccurrences, prependingEntity, removingBeginningOfEntity, removingEndOfEntity, rightWindow, scoreOf, scoresOf, setInitialSequence, splittingTwoEntities, toArray, toString, toString, updateSequenceElement

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

SeminarsPrior

public SeminarsPrior(java.lang.String backgroundSymbol,
                     Index<java.lang.String> classIndex,
                     java.util.List<IN> doc)

Method Detail

scoreOf

public double scoreOf(int[] sequence)

Description copied from interface: SequenceModel

Computes the score assigned by this model to the whole sequence. Typically this will be an unnormalized probability in log space (since the probabilities are small).

Parameters:

sequence - the sequence to compute a score for

Returns:

the score for the sequence