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See:
Description
| Interface Summary | |
|---|---|
| CharSeqCounter | A CharSeqCounter counter provides counts for sequences
of characters. |
| IntSeqCounter | An IntSeqCounter provides counts for sequences of
integers. |
| LanguageModel | A LanguageModel provides an estimate of the probability of a
sequence of characters. |
| LanguageModel.Conditional | A LanguageModel.Conditional is a language model
that implements conditional estimates of characters given
previous characters. |
| LanguageModel.Dynamic | A LanguageModel.Dynamic accepts training events in
the form of character slices or sequences. |
| LanguageModel.Process | A LanguageModel.Process is normalized by length. |
| LanguageModel.Sequence | A LanguageModel.Sequence is normalized over all
character sequences. |
| LanguageModel.Tokenized | A LanguageModel.Tokenized provides a means of
estimating the probability of a sequence of tokens. |
| TrieReader | The TrieReader interface provides a means to read a
trie structure with counts. |
| TrieWriter | The TrieWriter interface provides a means
to write an arbitrary trie structure with positive node counts. |
| Class Summary | |
|---|---|
| BitTrieReader | A BitTrieReader provides a trie reader that wraps a
bit-level input. |
| BitTrieWriter | A BitTrieWriter provides a trie writer that wraps a
bit-level output. |
| CharSeqMultiCounter | A CharSeqMultiCounter combines the counts from a pair
of character sequence counters. |
| CompiledNGramBoundaryLM | A CompiledNGramBoundaryLM is constructed by reading
the serialized form of an instance of NGramBoundaryLM. |
| CompiledNGramProcessLM | A CompiledNGramProcessLM implements a conditional
process language model. |
| CompiledTokenizedLM | A CompiledTokenizedLM implements a tokenized bounded
sequence language model. |
| MultiTrieReader | A MultiTrieReader merges two trie readers, providing
output that is the result of adding the counts from the two readers. |
| NGramBoundaryLM | An NGramBoundaryLM provides a dynamic sequence
language model for which training, estimation and pruning may be
interleaved. |
| NGramProcessLM | An NGramProcessLM provides a dynamic conditional
process language model process for which training, estimation, and
pruning may be interleaved. |
| PruneTrieReader | A PruneTrieReader filters a contained trie
reader by removing all subtrees whose counts fall below
a specified minimum. |
| ScaleTrieReader | A ScaleTrieReader filters a contained trie reader by
scaling all counts by a given multiple, removing all subtrees with
zero root counts. |
| TokenizedLM | A TokenizedLM provides a dynamic sequence language
model which models token sequences with an n-gram model, and
whitespace and unknown tokens with their own sequence language
models. |
| TrieCharSeqCounter | A TrieCharSeqCounter stores counts for substrings of
strings. |
| TrieIntSeqCounter | An TrieIntSeqCounter implements an integer sequence
counter with a trie structure of counts. |
| UniformBoundaryLM | A UniformBoundaryLM implements a uniform sequence
language model with a specified number of outcomes and the same
probability assigned to the end-of-stream marker. |
| UniformProcessLM | A UniformLM.Sequence implements a uniform sequence
language model with a specified number of outcomes and the same
probability assigned to the end-of-stream marker. |
Classes for character- and token-based language models.
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