| Package | Description |
|---|---|
| com.aliasi.classify |
Classes for classifying data and evaluation.
|
| com.aliasi.cluster |
Classes for clustering data and evaluation.
|
| com.aliasi.crf |
Classes and interfaces for conditional random fields.
|
| com.aliasi.dca |
Classes for fitting and running discrete choice analysis (DCA) models.
|
| com.aliasi.features |
Classes for extracting feature vectors from objects and parsing
objects for feature handlers.
|
| com.aliasi.hmm |
Classes for estimating and decoding hidden Markov models.
|
| com.aliasi.lm |
Classes for character- and token-based language models.
|
| com.aliasi.symbol |
Classes for string-based symbol tables.
|
| com.aliasi.tag |
Classes and interfaces for sequence tagging, including evaluators.
|
| com.aliasi.test.unit.symbol |
| Modifier and Type | Method and Description |
|---|---|
SymbolTable |
LogisticRegressionClassifier.featureSymbolTable()
Returns an unmodifiable view of the symbol table used for
features in this classifier.
|
| Modifier and Type | Method and Description |
|---|---|
static int[] |
LatentDirichletAllocation.tokenizeDocument(CharSequence text,
TokenizerFactory tokenizerFactory,
SymbolTable symbolTable)
Tokenizes the specified text document using the specified tokenizer
factory returning only tokens that exist in the symbol table.
|
static int[][] |
LatentDirichletAllocation.tokenizeDocuments(CharSequence[] texts,
TokenizerFactory tokenizerFactory,
SymbolTable symbolTable,
int minCount)
Tokenize an array of text documents represented as character
sequences into a form usable by LDA, using the specified
tokenizer factory and symbol table.
|
| Modifier and Type | Method and Description |
|---|---|
SymbolTable |
ChainCrf.featureSymbolTable()
Returns an unmodifiable view of the symbol table for features for
this CRF.
|
SymbolTable |
ForwardBackwardTagLattice.tagSymbolTable() |
| Constructor and Description |
|---|
ChainCrf(String[] tags,
boolean[] legalTagStarts,
boolean[] legalTagEnds,
boolean[][] legalTagTransitions,
Vector[] coefficients,
SymbolTable featureSymbolTable,
ChainCrfFeatureExtractor<E> featureExtractor,
boolean addInterceptFeature)
Construct a conditional random field from the specified tags,
feature vector coefficients, symbol table for feature, feature
extractors and flag indicating whether to add intercepts or
not.
|
ChainCrf(String[] tags,
Vector[] coefficients,
SymbolTable featureSymbolTable,
ChainCrfFeatureExtractor<E> featureExtractor,
boolean addInterceptFeature)
Construct a conditional random field from the specified tags,
feature vector coefficients, symbol table for feature, feature
extractors and flag indicating whether to add intercepts or
not.
|
| Modifier and Type | Method and Description |
|---|---|
SymbolTable |
DiscreteObjectChooser.featureSymbolTable()
Returns an unmodifiable view of the feature symbol
table underlying this chooser.
|
| Constructor and Description |
|---|
DiscreteObjectChooser(FeatureExtractor<E> featureExtractor,
SymbolTable featureSymbolTable,
DiscreteChooser chooser)
Construct a discrete chooser based on the specified feature
extractor, feature symbol table, and base chooser.
|
| Modifier and Type | Method and Description |
|---|---|
static Vector |
Features.toVector(Map<String,? extends Number> featureVector,
SymbolTable table,
int numDimensions,
boolean addIntercept)
Convert the specified feature vector into a sparse float vector using
the specified symbol table to encode features as integers.
|
static Vector |
Features.toVectorAddSymbols(Map<String,? extends Number> featureVector,
SymbolTable table,
int numDimensions,
boolean addIntercept)
Convert the specified feature vector into a sparse float vector
using the specified symbol table to encode features as
integers, adding features to the symbol table if necessary.
|
| Modifier and Type | Method and Description |
|---|---|
SymbolTable |
AbstractHmm.stateSymbolTable()
Return the symbol table for the states for this HMM.
|
SymbolTable |
HiddenMarkovModel.stateSymbolTable()
Return the symbol table for the states for this HMM.
|
| Constructor and Description |
|---|
AbstractHmm(SymbolTable stateSymbolTable)
Construct an HMM with the specified symbol table.
|
AbstractHmmEstimator(SymbolTable table)
Construct an HMM estimator with the specified tag symbol table.
|
| Modifier and Type | Method and Description |
|---|---|
SymbolTable |
TokenizedLM.symbolTable()
Returns the symbol table underlying this tokenized language
model's token n-gram model.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MapSymbolTable
A
MapSymbolTable is a dynamic symbol table based on a
pair of underlying maps. |
class |
SymbolTableCompiler
A
SymbolTableCompiler collects symbols represented as
String instances and compiles them into a SymbolTable. |
| Modifier and Type | Method and Description |
|---|---|
static SymbolTable |
SymbolTableCompiler.asSymbolTable(String[] symbols)
Returns a compiled symbol table constructed from the specified
list of symbols with symbol identifiers determined by array
position.
|
static SymbolTable |
MapSymbolTable.unmodifiableView(SymbolTable table)
Returns a view of the specified symbol table that cannot be
modified.
|
| Modifier and Type | Method and Description |
|---|---|
static SymbolTable |
MapSymbolTable.unmodifiableView(SymbolTable table)
Returns a view of the specified symbol table that cannot be
modified.
|
| Modifier and Type | Method and Description |
|---|---|
abstract SymbolTable |
TagLattice.tagSymbolTable()
Returns a symbol table which converts tags to identifiers and
vice-versa.
|
| Modifier and Type | Method and Description |
|---|---|
protected void |
AbstractSymbolTable.assertTwoElementTable(SymbolTable table) |
Copyright © 2016 Alias-i, Inc.. All rights reserved.