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MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.

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/* 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 [email protected]
*/

package cc.mallet.fst.confidence;

import cc.mallet.fst.*;
import cc.mallet.types.*;

/**
 * Estimates the confidence of a {@link Segment} extracted by a {@link
 * Transducer} by performing a "constrained lattice"
 * calculation. Essentially, this sums all possible ways this segment
 * could have been extracted and normalizes.
 */
public class ConstrainedForwardBackwardConfidenceEstimator extends TransducerConfidenceEstimator
{
	public ConstrainedForwardBackwardConfidenceEstimator (Transducer model) {
		super(model);
	}
	
	/**
		 Calculates the confidence in the tagging of a {@link Segment}.
		 @return 0-1 confidence value. higher = more confident.
	 */
	public double estimateConfidenceFor (Segment segment, SumLatticeDefault cachedLattice) {
		Sequence predSequence = segment.getPredicted ();
		Sequence input = segment.getInput ();
		SumLatticeDefault lattice = (cachedLattice == null) ? new SumLatticeDefault (model, input) : cachedLattice;
		// constrained lattice
		SumLatticeDefault constrainedLattice = new SumLatticeConstrained (model, input, null, segment, predSequence);
		double latticeWeight = lattice.getTotalWeight ();
		double constrainedLatticeWeight = constrainedLattice.getTotalWeight ();
		double confidence = Math.exp (latticeWeight - constrainedLatticeWeight);
		//System.err.println ("confidence: " + confidence);
		return confidence;
	}
	
	private static final long serialVersionUID = 1L;

}