Package opennlp.tools.ml.model
Interface SequenceClassificationModel
- All Known Implementing Classes:
BeamSearch
public interface SequenceClassificationModel
A classification model that can label an input
Sequence.-
Method Summary
Modifier and TypeMethodDescription<T> SequencebestSequence(T[] sequence, Object[] additionalContext, BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) Finds theSequencewith the highest probability.<T> Sequence[]bestSequences(int numSequences, T[] sequence, Object[] additionalContext, double minSequenceScore, BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) Finds the n most probablesequenceswith the highest probability.<T> Sequence[]bestSequences(int numSequences, T[] sequence, Object[] additionalContext, BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) Finds the n most probablesequenceswith the highest probability.String[]
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Method Details
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bestSequence
<T> Sequence bestSequence(T[] sequence, Object[] additionalContext, BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) Finds theSequencewith the highest probability.- Parameters:
sequence- Thesequenceused as input.additionalContext- An array that provides additional information (context).cg- TheBeamSearchContextGeneratorto use.validator- TheSequenceValidatorto validate with.- Returns:
- The
Sequencewith the highest probability.
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bestSequences
<T> Sequence[] bestSequences(int numSequences, T[] sequence, Object[] additionalContext, double minSequenceScore, BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) Finds the n most probablesequenceswith the highest probability.- Parameters:
numSequences- The number of sequences to compute.sequence- Thesequenceused as input.additionalContext- An array that provides additional information (context).minSequenceScore- The minimum score to achieve.cg- TheBeamSearchContextGeneratorto use.validator- TheSequenceValidatorto validate with.- Returns:
- The
sequenceswith the highest probability.
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bestSequences
<T> Sequence[] bestSequences(int numSequences, T[] sequence, Object[] additionalContext, BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) Finds the n most probablesequenceswith the highest probability.- Parameters:
numSequences- The number of sequences to compute.sequence- Thesequenceused as input.additionalContext- An array that provides additional information (context).cg- TheBeamSearchContextGeneratorto use.validator- TheSequenceValidatorto validate with.- Returns:
- The
sequenceswith the highest probability.
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getOutcomes
String[] getOutcomes()- Returns:
- Retrieves all possible outcomes.
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