public ConfidenceEvaluator (Segment[] segments, boolean sorted) { this.confidences = new Vector (); for (int i=0; i < segments.length; i++) { confidences.add (new EntityConfidence (segments[i].getConfidence(), segments[i].correct(), segments[i].getInput(), segments[i].getStart(), segments[i].getEnd())); } if (!sorted) Collections.sort (confidences, new ConfidenceComparator()); this.nBins = DEFAULT_NUM_BINS; this.numCorrect = getNumCorrectEntities (); }
public ConfidenceEvaluator (Segment[] segments, boolean sorted) { this.confidences = new Vector (); for (int i=0; i < segments.length; i++) { confidences.add (new EntityConfidence (segments[i].getConfidence(), segments[i].correct(), segments[i].getInput(), segments[i].getStart(), segments[i].getEnd())); } if (!sorted) Collections.sort (confidences, new ConfidenceComparator()); this.nBins = DEFAULT_NUM_BINS; this.numCorrect = getNumCorrectEntities (); }
public ConfidenceEvaluator (Segment[] segments, boolean sorted) { this.confidences = new Vector (); for (int i=0; i < segments.length; i++) { confidences.add (new EntityConfidence (segments[i].getConfidence(), segments[i].correct(), segments[i].getInput(), segments[i].getStart(), segments[i].getEnd())); } if (!sorted) Collections.sort (confidences, new ConfidenceComparator()); this.nBins = DEFAULT_NUM_BINS; this.numCorrect = getNumCorrectEntities (); }
public boolean equals (Object o) { Segment s = (Segment) o; if (start == s.getStart() && end == s.getEnd() && correct == s.correct() && input.size() == s.getInput().size()) { for (int i=start; i <= end; i++) { if (!pred.get( i ).equals( s.getPredicted( i ) ) || !truth.get( i ).equals( s.getTruth( i ) ) ) return false; } return true; } return false; } }
public boolean equals (Object o) { Segment s = (Segment) o; if (start == s.getStart() && end == s.getEnd() && correct == s.correct() && input.size() == s.getInput().size()) { for (int i=start; i <= end; i++) { if (!pred.get( i ).equals( s.getPredicted( i ) ) || !truth.get( i ).equals( s.getTruth( i ) ) ) return false; } return true; } return false; } }
public boolean equals (Object o) { Segment s = (Segment) o; if (start == s.getStart() && end == s.getEnd() && correct == s.correct() && input.size() == s.getInput().size()) { for (int i=start; i <= end; i++) { if (!pred.get( i ).equals( s.getPredicted( i ) ) || !truth.get( i ).equals( s.getTruth( i ) ) ) return false; } return true; } return false; } }
for (int c = 0; c < constraints.length; c++) constraints[c] = 0; for (int i=requiredSegment.getStart (); i <= requiredSegment.getEnd(); i++) { int si = t.stateIndexOfString ((String)constrainedSequence.get (i)); if (si == -1)
for (int c = 0; c < constraints.length; c++) constraints[c] = 0; for (int i=requiredSegment.getStart (); i <= requiredSegment.getEnd(); i++) { int si = t.stateIndexOfString ((String)constrainedSequence.get (i)); if (si == -1)
String[] sequence = new String[truth.size()]; for (int j=0; j < truth.size(); j++) { if (j <= leastConfidentSegment.getEnd() && j >= leastConfidentSegment.getStart()) sequence[j] = (String)truth.get (j); else sequence[j] = (String) predicted.get (j);
String[] sequence = new String[truth.size()]; for (int j=0; j < truth.size(); j++) { if (j <= leastConfidentSegment.getEnd() && j >= leastConfidentSegment.getStart()) sequence[j] = (String)truth.get (j); else sequence[j] = (String) predicted.get (j);
for (int c = 0; c < constraints.length; c++) constraints[c] = 0; for (int i=requiredSegment.getStart (); i <= requiredSegment.getEnd(); i++) { int si = t.stateIndexOfString ((String)constrainedSequence.get (i)); if (si == -1)
String[] sequence = new String[truth.size()]; for (int j=0; j < truth.size(); j++) { if (j <= leastConfidentSegment.getEnd() && j >= leastConfidentSegment.getStart()) sequence[j] = (String)truth.get (j); else sequence[j] = (String) predicted.get (j);
for (int c = 0; c < constraints.length; c++) constraints[c] = 0; for (int i=requiredSegment.getStart (); i <= requiredSegment.getEnd(); i++) { int si = t.stateIndexOfString ((String)constrainedSequence.get (i)); if (si == -1)
for (int c = 0; c < constraints.length; c++) constraints[c] = 0; for (int i=requiredSegment.getStart (); i <= requiredSegment.getEnd(); i++) { int si = t.stateIndexOfString ((String)constrainedSequence.get (i)); if (si == -1)
/** 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; double confidence = 1; for (int i=segment.getStart(); i <= segment.getEnd(); i++) confidence *= lattice.getGammaProbability (i+1, model.getState (stateIndexOfString ((String)predSequence.get (i)))); return confidence; }
/** 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; double confidence = 1; for (int i=segment.getStart(); i <= segment.getEnd(); i++) confidence *= lattice.getGammaProbability (i+1, model.getState (stateIndexOfString ((String)predSequence.get (i)))); return confidence; }
/** 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; double confidence = 1; for (int i=segment.getStart(); i <= segment.getEnd(); i++) confidence *= lattice.getGammaProbability (i+1, model.getState (stateIndexOfString ((String)predSequence.get (i)))); return confidence; }
/** 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; double confidence = 0; for (int i=segment.getStart(); i <= segment.getEnd(); i++) { int stateIndex = stateIndexOfString((String)predSequence.get(i)); if (stateIndex == -1) // Unknown label. return 0.0; confidence += lattice.getGammaProbability(i+1, model.getState(stateIndex)); } return confidence/(double)segment.size(); }
/** 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; double confidence = 0; for (int i=segment.getStart(); i <= segment.getEnd(); i++) { int stateIndex = stateIndexOfString((String)predSequence.get(i)); if (stateIndex == -1) // Unknown label. return 0.0; confidence += lattice.getGammaProbability(i+1, model.getState(stateIndex)); } return confidence/(double)segment.size(); }
/** 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; double confidence = 0; for (int i=segment.getStart(); i <= segment.getEnd(); i++) { int stateIndex = stateIndexOfString((String)predSequence.get(i)); if (stateIndex == -1) // Unknown label. return 0.0; confidence += lattice.getGammaProbability(i+1, model.getState(stateIndex)); } return confidence/(double)segment.size(); }