/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept.
This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit).
http://www.cs.umass.edu/~mccallum/mallet
This software is provided under the terms of the Common Public License,
version 1.0, as published by http://www.opensource.org. For further
information, see the file `LICENSE' included with this distribution. */
/**
@author Aron Culotta <a href="mailto:culotta@cs.umass.edu">culotta@cs.umass.edu</a>
*/
package cc.mallet.fst.confidence;
import java.util.logging.*;
import java.util.*;
import cc.mallet.fst.*;
import cc.mallet.pipe.iterator.*;
import cc.mallet.types.*;
import cc.mallet.util.MalletLogger;
/**
Estimates the confidence of an entire sequence by the probability
of the Viterbi path normalized by the probabliity of the entire
lattice.
*/
public class ViterbiConfidenceEstimator extends TransducerSequenceConfidenceEstimator
{
private static Logger logger = MalletLogger.getLogger(
ViterbiConfidenceEstimator.class.getName());
public ViterbiConfidenceEstimator (Transducer model) {
super(model);
}
/**
Calculates the confidence in the tagging of a {@link Instance}.
*/
public double estimateConfidenceFor (Instance instance,
Object[] startTags,
Object[] inTags) {
SumLatticeDefault lattice = new SumLatticeDefault (model, (Sequence)instance.getData());
SequencePairAlignment viterbi = new MaxLatticeDefault (model, (Sequence)instance.getData()).bestOutputAlignment();
return Math.exp (viterbi.getWeight() - lattice.getTotalWeight());
}
}