| Package | Description |
|---|---|
| com.aliasi.chunk |
Classes for extracting meaningful chunks (spans) of text.
|
| com.aliasi.classify |
Classes for classifying data and evaluation.
|
| com.aliasi.dict |
Classes for handling dictionaries.
|
| com.aliasi.hmm |
Classes for estimating and decoding hidden Markov models.
|
| com.aliasi.lm |
Classes for character- and token-based language models.
|
| com.aliasi.spell |
Classes for spelling correction and edit distance.
|
| com.aliasi.stats |
Classes for handling basic statical distributions and estimators.
|
| com.aliasi.symbol |
Classes for string-based symbol tables.
|
| com.aliasi.tag |
Classes and interfaces for sequence tagging, including evaluators.
|
| com.aliasi.test.unit.chunk | |
| com.aliasi.tokenizer |
Classes for tokenizing character sequences.
|
| com.aliasi.util |
Classes for general Java utilities.
|
| Modifier and Type | Class and Description |
|---|---|
class |
CharLmHmmChunker
A
CharLmHmmChunker employs a hidden Markov model
estimator and tokenizer factory to learn a chunker. |
class |
CharLmRescoringChunker
A
CharLmRescoringChunker provides a long-distance
character language model-based chunker that operates by rescoring
the output of a contained character language model HMM chunker. |
class |
RegExChunker
A
RegExChunker finds chunks that matches regular
expressions. |
class |
TrainTokenShapeChunker
A
TrainTokenShapeChunker is used to train a token and
shape-based chunker. |
| Modifier and Type | Class and Description |
|---|---|
class |
BinaryLMClassifier
A
BinaryLMClassifier is a boolean dynamic language
model classifier for use when there are two categories, but
training data is only available for one of the categories. |
class |
DynamicLMClassifier<L extends LanguageModel.Dynamic>
A
DynamicLMClassifier is a language model classifier
that accepts training events of categorized character sequences. |
class |
KnnClassifier<E>
A
KnnClassifier implements k-nearest-neighor
classification based on feature extraction and a vector proximity
or distance. |
class |
LogisticRegressionClassifier<E>
A
LogisticRegressionClassifier provides conditional
probability classifications of input objects using an underlying
logistic regression model and feature extractor. |
class |
NaiveBayesClassifier
A
NaiveBayesClassifier provides a trainable naive Bayes
text classifier, with tokens as features. |
class |
TfIdfClassifierTrainer<E>
A
TfIdfClassifierTrainer provides a framework for
training discriminative classifiers based on term-frequency (TF)
and inverse document frequency (IDF) weighting of features. |
class |
TradNaiveBayesClassifier
A
TradNaiveBayesClassifier implements a traditional
token-based approach to naive Bayes text classification. |
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractDictionary<C>
An
AbstractDictionary is a dictionary with convenience
implementations of most methods. |
class |
DictionaryEntry<C>
A
DictionaryEntry provides a phrase as a string, an
object-based category for the phrase, and a double-valued score. |
class |
MapDictionary<C>
A
MapDictionary uses an underlying map from phrases to
their set of dictionary entries. |
class |
TrieDictionary<C>
A
TrieDictionary stores a dictionary using a character
trie structure. |
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractHmmEstimator
An
HmmEstimator may be used to train a hidden Markov
model (HMM). |
class |
HmmCharLmEstimator
An
HmmCharLmEstimator employs a maximum a posteriori
transition estimator and a bounded character language model
emission estimator. |
| Modifier and Type | Interface and Description |
|---|---|
static interface |
LanguageModel.Dynamic
A
LanguageModel.Dynamic accepts training events in
the form of character slices or sequences. |
| Modifier and Type | Class and Description |
|---|---|
class |
NGramBoundaryLM
An
NGramBoundaryLM provides a dynamic sequence
language model for which training, estimation and pruning may be
interleaved. |
class |
NGramProcessLM
An
NGramProcessLM provides a dynamic conditional
process language model process for which training, estimation, and
pruning may be interleaved. |
class |
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. |
class |
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. |
class |
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. |
| Modifier and Type | Class and Description |
|---|---|
class |
FixedWeightEditDistance
A
FixedWeightEditDistance sets constant weights for
the edit operations for weighted edit distance. |
class |
TrainSpellChecker
A
TrainSpellChecker instance provides a mechanism for
collecting training data for a compiled spell checker. |
| Modifier and Type | Class and Description |
|---|---|
class |
BernoulliEstimator
A
BernoulliEstimator provides a maximum likelihood
estimate of a Bernoulli distribution. |
class |
LogisticRegression
A
LogisticRegression instance is a multi-class vector
classifier model generating conditional probability estimates of
categories. |
| Modifier and Type | Class and Description |
|---|---|
class |
SymbolTableCompiler
A
SymbolTableCompiler collects symbols represented as
String instances and compiles them into a SymbolTable. |
| Modifier and Type | Class and Description |
|---|---|
class |
ClassifierTagger<E>
A
ClassifierTagger implements the first-best tagger
interface with a classifier that operates left-to-right
over the tokens, classifying one token at a time. |
| Modifier and Type | Method and Description |
|---|---|
static <C extends Chunker & Compilable> |
CharLmHmmChunkerTest.assertChunkingCompile(C chunkerEstimator,
Chunking expectedChunking) |
| Modifier and Type | Class and Description |
|---|---|
class |
IndoEuropeanTokenCategorizer
A
IndoEuropeanTokenCategorizer is a generic token
categorizer for Indo-European languages that is based on character
"shape". |
| Modifier and Type | Method and Description |
|---|---|
static Object |
AbstractExternalizable.compile(Compilable c)
Return the compiled form of the specified compilable.
|
static void |
AbstractExternalizable.compileTo(Compilable compilable,
File file)
Compiles the specified compilable object to the specified file.
|
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