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a.
a element with no attributes.
a element with the specified
attributes.
a element with the specified
attribute and value.
a element with the specified
attributes and values.
a element with the specified
attributes and values.
a element with the specified
attributes and values.
abbr.
abbr element with no attributes.
abbr element with the specified
attributes.
abbr element with the specified
attribute and value.
abbr element with the specified
attributes and values.
abbr element with the specified
attributes and values.
abbr element with the specified
attributes and values.
abbr attribute.
Abstract element.
AbstractText element.
AbstractCharLmRescoringChunker provides the basic
character language-model rescoring model used by the trainable
CharLmRescoringChunker and its compiled version.CommandLineArguments object represents a the
command-line arguments.AbstractDictionary is a dictionary with convenience
implementations of most methods.AbstractDiscreteDistribution provides a default
abstract implementation of discrete distributions.AbstractExternalizer is an adapter for read
resolved externalizables.AbstractHierachicalClusterer provides an adapter
for clustering for hierarchical clusterers.AbstractHmm is an abstract implementation of a
hidden Markov model which manages a symbol table and defines the
basic methods in terms of the symbolic linear probability methods.HmmEstimator may be used to train a hidden Markov
model (HMM).AbstractMatrix implements most of a matrix's
functionality in terms of methods for accessing numbers of rows and
columns and values.AbstractMentionFactory class implements the
mention factory interface using linguistically-motivated abstract
methods.AbstractSentenceModel implements a sentence model
in terms of the method that adds indices to the collection.AbstractVector implements most of a vector's
functionality in terms of methods for dimensionality and values.true if the specified file name has
an acceptable suffix as specified in the constructor.
true if a file is acceptable to this
filter.
true if files with the specified
name should be accepted.
true for objects returned by the contained
iterator that should be returned by this iterator.
accept attribute.
accept-charset attribute.
AccessionNumber element.
accesskey attribute.
acronym.
acronym element with no attributes.
acronym element with the specified
attributes.
acronym element with the specified
attribute and value.
acronym element with the specified
attributes and values.
acronym element with the specified
attributes and values.
acronym element with the specified
attributes and values.
Acronym element.
action attribute.
AbstractMentionChain.add(Mention), which may be overridden
by subclasses to carry out additional bookkeeping when
new mentions are added.
BoundedPriorityQueue.offer(Object) instead. In the next
release, this will be redefined to match the collection
interface.
ShortPriorityQueue.offer(Object) instead.
java.util.Collections.addAll(Collection,Object[]) instead.
ClassifierEvaluator.handle(Classified) instead.
null.
AddFeatureExtractor returns feature vectors that result
from summing the feature vectors returned by a collection of
contained feature extractors.true if this classifier automatically adds
an intercept feature to each feature vector.
true if this CRF adds an intercept feature
with value 1.0 at index 0 to all feature vectors.
address.
address element with no attributes.
address element with the specified
attributes.
address element with the specified
attribute and value.
address element with the specified
attributes and values.
address element with the specified
attributes and values.
address element with the specified
attributes and values.
"CDATA".
Affiliation element.
Agency element.
align attribute.
true if all of the characters
making up the specified string are digits.
true if all of the characters
in the specified range are digits.
true if all of the characters in the
specified array are letters.
true if all of the characters in the
specified array are lower case letters.
true if the specified character sequence
contains only lowercase letters.
true if this spell checker allows
deletions.
true if this spell checker allows
insertions.
true if this spell checker allows
matches.
true if this spell checker allows
substitutions.
true if this spell checker allows
transpositions.
true if all of the characters in the
specified array are punctuation as specified by
Strings.isPunctuation(char).
true if all of the characters in the
specified string are punctuation as specified by
Strings.isPunctuation(char).
true if none of the characters in the
specified array are letters or digits.
true if all of the characters in the
specified array are upper case letters.
true if the specified buffer contains
only whitespace characters.
true if the specified string contains
only whitespace characters.
true if the specified range of the
specified character array only whitespace characters, as defined for
characters by Strings.isWhitespace(char c).
alt attribute.
AnnealingSchedule instance implements a method to
return the learning rate for a specified epoch.applet.
applet element with no attributes.
applet element with the specified
attributes.
applet element with the specified
attribute and value.
applet element with the specified
attributes and values.
applet element with the specified
attributes and values.
applet element with the specified
attributes and values.
ApproxDictionaryChunker implements a chunker that
produces chunks based on weighted edit distance of strings from
dictionary entries.archive attribute.
area.
area element with no attributes.
area element with the specified
attributes.
area element with the specified
attribute and value.
area element with the specified
attributes and values.
area element with the specified
attributes and values.
area element with the specified
attributes and values.
Article element.
ArticleTitle element.
true if the article has been translated
from a language other than English.
Exceptions.finiteNonNegative(String,double)
instead.
Author element.
AuthorList element.
AutoCompleter maintains a dictionary of phrases with
counts and provides suggested completions based on prefix matching
by weighted edit distance and phrase likelihood.axis attribute.
b.
b element with no attributes.
b element with the specified
attributes.
b element with the specified
attribute and value.
b element with the specified
attributes and values.
b element with the specified
attributes and values.
b element with the specified
attributes and values.
"B-GENE".
true if this model does parenthesis
balancing.
base.
base element with no attributes.
base element with the specified
attributes.
base element with the specified
attribute and value.
base element with the specified
attributes and values.
base element with the specified
attributes and values.
base element with the specified
attributes and values.
BaseClassifier interface specifies a single method for
first-best classification.BaseClassifierEvaluator provides an evaluation harness
for first-best classifiers.basefont.
basefont element with no attributes.
basefont element with the specified
attributes.
basefont element with the specified
attribute and value.
basefont element with the specified
attributes and values.
basefont element with the specified
attributes and values.
basefont element with the specified
attributes and values.
bdo.
bdo element with no attributes.
bdo element with the specified
attributes.
bdo element with the specified
attribute and value.
bdo element with the specified
attributes and values.
bdo element with the specified
attributes and values.
bdo element with the specified
attributes and values.
"B_".
"B-".
BernoulliClassifier provides a feature-based
classifier where feature values are reduced to booleans based on a
specified threshold.BernoulliConstant implements a Bernoulli
distribution with a constant probability of success.BernoulliDistribution is a multivariate distribution
with two outcomes, 0 (labeled "failure") and 1 (labeled "success").BernoulliEstimator provides a maximum likelihood
estimate of a Bernoulli distribution.big.
big element with no attributes.
big element with the specified
attributes.
big element with the specified
attribute and value.
big element with the specified
attributes and values.
big element with the specified
attributes and values.
big element with the specified
attributes and values.
BigVectorClassifier provides an efficient linear
classifier implementation for large numbers of categories.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.BinaryMap class implements a map from objects to
integer objects where the only value is the integer with value 1.BinomialDistribution is a discrete distribution over
the number of successes given a fixed number of Bernoulli trials.BioTagChunkCodec implements a chunk to tag
coder/decoder based on the BIO encoding scheme and a
specified tokenizer factory.BitInput wraps an underlying input stream to provide
bit-level input.BitOutput wraps an underlying output stream to
provide bit-level output.BitTrieReader provides a trie reader that wraps a
bit-level input.BitTrieWriter provides a trie writer that wraps a
bit-level output.blockquote.
blockquote element with no attributes.
blockquote element with the specified
attributes.
blockquote element with the specified
attribute and value.
blockquote element with the specified
attributes and values.
blockquote element with the specified
attributes and values.
blockquote element with the specified
attributes and values.
body.
body element with no attributes.
body element with the specified
attributes.
body element with the specified
attribute and value.
body element with the specified
attributes and values.
body element with the specified
attributes and values.
body element with the specified
attributes and values.
Matcher that returns a
constant value if a boolean condition is satisifed and the no-match
score otherwise.border attribute.
Integer
instances to the specified collection, only considering tokens
between index start and end-1
inclusive.
Integer
instances to the specified collection, only considering tokens
between index start and end-1
inclusive.
Integer
instances to the specified collection, only considering tokens
between index start and end-1
inclusive.
BoundedFeatureExtractor provides a lower-bound and
upper-bound on feature values between which all values from a
contained base extractor are bounded.BoundedPriorityQueue implements a priority queue
with an upper bound on the number of elements.br.
br element with no attributes.
br element with the specified
attributes.
br element with the specified
attribute and value.
br element with the specified
attributes and values.
br element with the specified
attributes and values.
br element with the specified
attributes and values.
null
if there are no more objects.
button.
button element with no attributes.
button element with the specified
attributes.
button element with the specified
attribute and value.
button element with the specified
attributes and values.
button element with the specified
attributes and values.
button element with the specified
attributes and values.
Integer.toHexString(b) instead.
CachedMention stores all of the retun values
specified by the Mention interface.CacheFeatureExtractor uses a cache to store a mapping from
objects to their feature vector maps.true if the first character in the
specified array is an upper case letter and all subsequent
characters are lower case letters.
caption.
caption element with no attributes.
caption element with the specified
attributes.
caption element with the specified
attribute and value.
caption element with the specified
attributes and values.
caption element with the specified
attributes and values.
caption element with the specified
attributes and values.
true if this dictionary chunker is
case sensitive.
AbstractDictionary.categoryEntryList(Object) instead.
Dictionary.categoryEntryList(Object) instead.
LMClassifier.categoryDistribution().
cellpadding attribute.
cellspacing attribute.
center.
center element with no attributes.
center element with the specified
attributes.
center element with the specified
attribute and value.
center element with the specified
attributes and values.
center element with the specified
attributes and values.
center element with the specified
attributes and values.
ChainCrf<E> class implements linear chain conditional
random field decoding and estimation for input token sequences of
type E.ChainCrfChunker implements chunking based on a chain CRF
over string sequences, a tokenizer factory, and a tag to chunk
coder/decoder.ChainCrfFeatureExtractor interface specifies a method
for conditional random fields to extract the necessary node and
edge features for estimation and tagging.ChainCrfFeatures interface specifies methods for
extracting node and edge features for a conditional random field.char attribute.
SAXFilterHandler.mHandler.
DefaultHandler.characters(char[],int,int) to handle the
characters.
DefaultHandler.characters(char[],int,int).
DefaultHandler.characters(char[],int,int) to handle the
characters.
DefaultHandler.characters(char[],int,int).
TextContentFilter.filteredCharacters(char[],int,int).
CharacterTokenCategorizer.INSTANCE instead.
CharacterTokenizerFactory considers each
non-whitespace character in the input to be a distinct token.CharacterTokenizerFactory.INSTANCE instead.
CharLmHmmChunker employs a hidden Markov model
estimator and tokenizer factory to learn a chunker.CharLmHmmChunker from the specified
tokenizer factory and hidden Markov model estimator.
CharLmHmmChunker from the specified
tokenizer factory, HMM estimator and tag-smoothing flag.
CharLmRescoringChunker provides a long-distance
character language model-based chunker that operates by rescoring
the output of a contained character language model HMM chunker.charoff attribute.
CharSeqCounter counter provides counts for sequences
of characters.CharSeqMultiCounter combines the counts from a pair
of character sequence counters.charset attribute.
checked attribute.
Chemical element.
ChemicalList element.
Chunk interface specifies a slice of a character
sequence, a chunk type and a chunk score.ChunkAndCharSeq is an immutable composite of a
chunk and a character sequence.Chunker interface specifies methods for returning
a chunking given a character sequence or character slice.ChunkerEvaulator class provides an evaluation
framework for chunkers.ChunkerFeatureExtractor implements a feature extractor
for character sequences based on a specified chunker.ChunkFactory provides static factory methods for
creating chunks from components.ObjectHandler<Chunking> instead.TagChunkCodecAdapters.taggingToChunking(TagChunkCodec,ObjectHandler)
instead.Chunking interface specifies a set of chunks
over a shared underlying character sequence.ChunkingEvaluation stores and reports the results of
evaluating response chunkings against reference chunkings.ChunkingImpl provides a mutable, set-based
implementation of the chunking interface.TagChunkCodecAdapters.chunkingToStringTagging(TagChunkCodec,ObjectHandler)
instead.CitationSubset element.
cite.
cite element with no attributes.
cite element with the specified
attributes.
cite element with the specified
attribute and value.
cite element with the specified
attributes and values.
cite element with the specified
attributes and values.
cite element with the specified
attributes and values.
cite attribute.
class attribute.
classid attribute.
Classification provides a first-best category.ObjectHandler with subclass of Classified<E> instead.Classified represents an object that has been classified
with a first-best classification.BaseClassifier or one if its subinterfaces.BaseClassifierEvaluator or one of its subclasses.Clusterer interface defines a means of clustering
a set of input elementsClusterScore provides a range of cluster scoring
metrics for reference partitions versus response partitions.code.
code element with no attributes.
code element with the specified
attributes.
code element with the specified
attribute and value.
code element with the specified
attributes and values.
code element with the specified
attributes and values.
code element with the specified
attributes and values.
codebase attribute.
Coden element.
codetype attribute.
col.
col element with no attributes.
col element with the specified
attributes.
col element with the specified
attribute and value.
col element with the specified
attributes and values.
col element with the specified
attributes and values.
col element with the specified
attributes and values.
colgroup.
colgroup element with no attributes.
colgroup element with the specified
attributes.
colgroup element with the specified
attribute and value.
colgroup element with the specified
attributes and values.
colgroup element with the specified
attributes and values.
colgroup element with the specified
attributes and values.
CollectionTitle element.
CollectiveName element.
TokenizedLM.collocationSet(int,int,int) instead.
cols attribute.
colspan attribute.
lingmed sandbox project.CommaSeparatedValues object represents a
two-dimensional array of strings which may be read and written in
comma-separated-value string representation.CommentsCorrections element.
CompactHashSet implements the set interface more tightly in
memory and more efficiently than Java's HashSet.Compilable interface specifies a general way in
which an object may be compiled to an object output.CompiledNGramBoundaryLM is constructed by reading
the serialized form of an instance of NGramBoundaryLM.CompiledNGramProcessLM implements a conditional
process language model.CompiledSpellChecker class implements a first-best
spell checker based on models of what users are likely to mean and
what errors they are likely to make in expressing their meaning.CompiledTokenizedLM implements a tokenized bounded
sequence language model.objOut.writeObject(this).
SymbolTableCompiler.compileTo(ObjectOutput).
Serializable interface instead.
Serializable interface instead.
Serializable interface instead.
Serializable interface instead.
true if the author list is complete.
true if the list of databank numbers in
the citation is complete.
CompleteYN attribute.
Completed value.
CompleteLinkClusterer implements complete link
agglomerative clustering.Strings.DEFAULT_SEPARATOR_STRING.
Strings.DEFAULT_SEPARATOR_STRING.
ConditionalClassification is a scored classification
which estimates conditional probabilities of categories given an
input.0.01.
0.01.
ConditionalClassifier interface specifies a single method
for n-best classification with conditional category probabilities.ConditionalClassifierEvaluator provides an evaluation
harness for conditional probability-based n-best classifiers.ConfidenceChunker interface specifies a method
for returning an iterator over chunks in order of confidence.ConfusionMatrix represents a
quantitative comparison between two classifiers over a fixed set of
categories on a number of test cases.true if the specified tokens and
whitespaces are consistent with the specified tokenizer
factory.
true if this dendrogram contains the
specified object as a leaf.
true if this set contains the specified object.
true if the specified string contains
an instance of the specified character.
true if at least one of the characters in
the specified array is a digit.
true if this mapping contains a mapping
for the specified object.
true if at least one of the characters in
the specified array is a letter.
true if this map contains a mapping
from some key to the specified value.
content attribute.
coords attribute.
CopyrightInformation element.
Corpus abstract class provides a basis for passing
training and testing data to data handlers.CosineDistance class implements proximity as
vector cosine.CountComparator that compares objects
based on their counts in this object to counter map.
0.
Country element.
java.io.File.createTempFile(String,String) instead.
data attribute.
DataBank element.
DataBankList element.
DataBankName element.
DateCompleted element.
DateCreated element.
DateRevised element.
null if it is still in process.
DatesAssociatedWithName element.
datetime attribute.
Day element.
dd.
dd element with no attributes.
dd element with the specified
attributes.
dd element with the specified
attribute and value.
dd element with the specified
attributes and values.
dd element with the specified
attributes and values.
dd element with the specified
attributes and values.
DecimalFormat directly with a pattern, or use the
newer Formatter class or String.format(String,Object[]) utility
method instead.
declare attribute.
Double.NEGATIVE_INFINITY.
"CHUNK".
"test".
"train".
defer attribute.
del.
del element with no attributes.
del element with the specified
attributes.
del element with the specified
attribute and value.
del element with the specified
attributes and values.
del element with the specified
attributes and values.
del element with the specified
attributes and values.
DelegateHandler may be used with a delegating
handler to more efficiently implement nested embeddings.DelegatingHandler is a SAX filter that routes events
to embedded handlers based on their element embedding.DeleteCitation element.
Dendrogram represents the result of a weighted
hierarchical clustering of a set of objects.DenseMatrix is a matrix implementation suitable for
matrices with primarily non-zero values.DenseVector is a vector implementation suitable for
vectors with primarily non-zero values.DescriptorName element.
dfn.
dfn element with no attributes.
dfn element with the specified
attributes.
dfn element with the specified
attribute and value.
dfn element with the specified
attributes and values.
dfn element with the specified
attributes and values.
dfn element with the specified
attributes and values.
Dictionary interface represents a dictionary as a
set of entries.DictionaryEntry provides a phrase as a string, an
object-based category for the phrase, and a double-valued score.1.
dir.
dir element with no attributes.
dir element with the specified
attributes.
dir element with the specified
attribute and value.
dir element with the specified
attributes and values.
dir element with the specified
attributes and values.
dir element with the specified
attributes and values.
dir attribute.
disabled attribute.
DiscreteChooser class implements multinomial
conditional logit discrete choice analysis with variables varying
over alternatives.DiscreteDistribution provides a probability
distribution over long integer outcomes.DiscreteObjectChooser provides an implementation of
discrete choice analysis (DCA) over arbitrary objects using a
feature extractor.DiskCorpus reads data from a specified training and
test directory using a specified parser.Distance interface provides a general method for
defining distances between two objects.div.
div element with no attributes.
div element with the specified
attributes.
div element with the specified
attribute and value.
div element with the specified
attributes and values.
div element with the specified
attributes and values.
div element with the specified
attributes and values.
dl.
dl element with no attributes.
dl element with the specified
attributes.
dl element with the specified
attribute and value.
dl element with the specified
attributes and values.
dl element with the specified
attributes and values.
dl element with the specified
attributes and values.
α for document distributions over topics
from which this sample was produced.
DotProductKernel is the trivial kernel function
computed by taking the dot product of the input vectors.dt.
dt element with no attributes.
dt element with the specified
attributes.
dt element with the specified
attribute and value.
dt element with the specified
attributes and values.
dt element with the specified
attributes and values.
dt element with the specified
attributes and values.
DynamicLMClassifier is a language model classifier
that accepts training events of categorized character sequences.EIdType attribute.
ELocationId element.
EditDistance class implements the standard notion
of edit distance, with or without transposition.Electronic-Print value for publication model.
ElectronicPubDate element.
Electronic value for publication model.
sb.append(c.toString()) instead.
TradNaiveBayesClassifier.emIterator(TradNaiveBayesClassifier,Factory,Corpus,Corpus,double) instead.
TradNaiveBayesClassifier.emTrain(TradNaiveBayesClassifier,Factory,Corpus,Corpus,double,int,double,Reporter) instead.
em.
em element with no attributes.
em element with the specified
attributes.
em element with the specified
attribute and value.
em element with the specified
attributes and values.
em element with the specified
attributes and values.
em element with the specified
attributes and values.
null if not caching.
null if not caching.
Attributes with no
attributes.
Strings.EMPTY_CHAR_ARRAY instead.
0 array of integers.
Strings.EMPTY_STRING_ARRAY instead.
enctype attribute.
EndPage element.
GroupCharactersFilter.characters(char[],int,int) on
any accumulated characters.
SAXFilterHandler.mHandler.
GroupCharactersFilter.characters(char[],int,int) to handle any accumulated
characters.
SAXFilterHandler.mHandler.
true if all of the available bits have
been read or if this stream has been closed.
SAXFilterHandler.mHandler.
null namespace, using
the local name for both local and qualified names.
null namespace, using the local name for both
local and qualified names.
true if this codec enforces consistency
of the chunkings relative to the tokenizer factory.
EnglishStopTokenizerFactory instead.EnglishStopTokenizerFactory or ModifyTokenTokenizerFactory.modify(Tokenizer) instead.
EnglishStopTokenizerFactory applies an English stop
list to a contained base tokenizer factory.null if the entity is undefined.
AbstractDictionary.entryList() instead.
Dictionary.entryList() instead.
true if the specified chunkings are equal.
true if the two character sequences have
the same length and the same characters.
true if the specified object is a chunk
that is equal to this chunk.
true if the specified object is a chunk
and character sequence structurally equivalent to this one.
true if the specified object is a chunking
equal to this one.
true if the specified object is a mention
chain that is equal to this mention chain.
true if the specified mention chain is
equal to this mention chain.
true if the specified object is a
dictionary object equal to this one.
true if the specified object is a matrix of
the same dimensionality with the same values.
true if the specified object is a vector
with the same dimensionality and values as this vector.
true if the specified object is a matrix
with the same number of rows and columns and the same value in
every cell as this matrix.
true if the specified object is a vector
that has the same dimensionality and values as this vector.
true if the specified object is a string
tagging that's structurally identical to this tagging.
true if the specified object is a tokenization
that is equal to this one.
true if the specified arrays are
the same length and contain the same elements.
true if the specified object
is a pair that has objects equal to this pair's.
true if the specified object is
a scored object with an object equal to this object's
and equal scores.
SAXFilterHandler.mHandler.
F pruned to the specified minimum feature count,
using the specified feature extractor, automatically adding an
intercept feature if the flag is true, allow unseen tag
transitions as specified, using the specified training
parameters for annealing, measuring convergence, and reporting
the incremental results to the specified reporter.
LogisticRegression.estimate(Vector[],int[],RegressionPrior,AnnealingSchedule,Reporter,double,int,int)
instead.
EuclideanDistance class implements standard
Euclidean distance between vectors.null if there is no period in the name.
CharacterTokenizerFactory.INSTANCE instead.
IndoEuropeanTokenizerFactory.INSTANCE instead.
Factory provides a generic interface for object
creation of a specified type."failure".
FastCache is a map implemented with soft references,
optimistic copy-on-write updates, and approximate count-based
pruning.SAXFilterHandler.mHandler.
FeatureExtractor provides a method of converting
generic input objects into feature vectors.FeatureExtractorFilter contains a reference to another
feature extractor.Features class contains static utility classes for
manipulating features.fieldset.
fieldset element with no attributes.
fieldset element with the specified
attributes.
fieldset element with the specified
attribute and value.
fieldset element with the specified
attributes and values.
fieldset element with the specified
attributes and values.
fieldset element with the specified
attributes and values.
FileLineReader instance represents the lines of a file.File.isFile().
Files.fileToURLName(file) use
file.toURI().toURL().toString().
null otherwise.
null to remove the feature altogether.
ZScoreFeatureExtractor.zScore(String,double) instead; this
method no longer overrides the the method of the same name in
ModifiedFeatureExtractor because this class no longer
overrides ModifiedFeatureExtractor.
ModifiedTokenizerFactory instead.BoundedPriorityQueue.remove() instead.
HmmDecoder.tag(List) instead.
java.util.Formatter instead.
FixedWeightEditDistance sets constant weights for
the edit operations for weighted edit distance.Fβ value for
the specified β.
font.
font element with no attributes.
font element with the specified
attributes.
font element with the specified
attribute and value.
font element with the specified
attributes and values.
font element with the specified
attributes and values.
font element with the specified
attributes and values.
for attribute.
true if this model treats any input-final
token as a stop.
ForeName element.
form.
form element with no attributes.
form element with the specified
attributes.
form element with the specified
attribute and value.
form element with the specified
attributes and values.
form element with the specified
attributes and values.
form element with the specified
attributes and values.
ForwardBackwardTagLattice provides an implementation of
a tag lattice based on forward, backward, transition and
normalizing values.frame.
frame element with no attributes.
frame element with the specified
attributes.
frame element with the specified
attribute and value.
frame element with the specified
attributes and values.
frame element with the specified
attributes and values.
frame element with the specified
attributes and values.
frame attribute.
frameset.
frameset element with no attributes.
frameset element with the specified
attributes.
frameset element with the specified
attribute and value.
frameset element with the specified
attributes and values.
frameset element with the specified
attributes and values.
frameset element with the specified
attributes and values.
TokenizedLM.frequentTermSet(int,int) instead.
GaussianRadialBasisKernel provides a kernel based on
a Gaussian radial basis function with a fixed variance parameter."GENE".
GeneSymbol element.
"GENE".
GeneralNote element.
abstract.
sentence.
sentence.
Integer with value 1 if the specified
argument is mapped to 1 by this map, and returns null
otherwise.
null if
there is no value attached.
null if
there is no value attached.
null if it does not exist.
null
if none has been specified.
Parser.getHandler() instead.
Parser.getHandler() instead.
Parser.getHandler() instead.
String.split(String) instead.
AbstractCommand.getArgument(String), but
throws an exception if the argument does not exist.
l.get(0) instead.
set.iterator().next() instead.
-1 if it is not a category for this
confusion matrix.
null
if none has been specified.
Parser.getHandler() instead.
Parser.getHandler().
Parser.getHandler() instead.
null
handler.
Grant element.
GrantID element.
GrantList element.
GroupCharactersFilter.characters(char[],int,int) into a single call with all of the
content concatenated.h1.
h1 element with no attributes.
h1 element with the specified
attributes.
h1 element with the specified
attribute and value.
h1 element with the specified
attributes and values.
h1 element with the specified
attributes and values.
h1 element with the specified
attributes and values.
h2.
h2 element with no attributes.
h2 element with the specified
attributes.
h2 element with the specified
attribute and value.
h2 element with the specified
attributes and values.
h2 element with the specified
attributes and values.
h2 element with the specified
attributes and values.
h3.
h3 element with no attributes.
h3 element with the specified
attributes.
h3 element with the specified
attribute and value.
h3 element with the specified
attributes and values.
h3 element with the specified
attributes and values.
h3 element with the specified
attributes and values.
h4.
h4 element with no attributes.
h4 element with the specified
attributes.
h4 element with the specified
attribute and value.
h4 element with the specified
attributes and values.
h4 element with the specified
attributes and values.
h4 element with the specified
attributes and values.
h5.
h5 element with no attributes.
h5 element with the specified
attributes.
h5 element with the specified
attribute and value.
h5 element with the specified
attributes and values.
h5 element with the specified
attributes and values.
h5 element with the specified
attributes and values.
h6.
h6 element with no attributes.
h6 element with the specified
attributes.
h6 element with the specified
attribute and value.
h6 element with the specified
attributes and values.
h6 element with the specified
attributes and values.
h6 element with the specified
attributes and values.
CharLmHmmChunker.handle(Chunking) instead.
CharLmRescoringChunker.handle(Chunking) instead.
BioTagChunkCodec instead.
TrainTokenShapeChunker.handle(Chunking) instead.
BernoulliClassifier.handle(Classified) instead.
ClassifierEvaluator.handle(Classified) instead.
DynamicLMClassifier.handle(Classified) instead.
KnnClassifier.handle(Classified) instead.
TfIdfClassifierTrainer.handle(Classified) instead.
TradNaiveBayesClassifier.handle(Classified) instead.
AbstractHmmEstimator.handle(Tagging) instead.
NGramBoundaryLM.handle(CharSequence) instead.
NGramProcessLM.handle(CharSequence) instead.
TokenizedLM.handle(CharSequence) instead.
TfIdfDistance.handle(CharSequence) instead.
TrainSpellChecker.handle(CharSequence) instead.
Handler marker interface indicates that a class
will be implement a handle method appropriate for a particular
Parser.HardFastCache is a map implemented with hard
references, optimistic copy-on-write updates, and approximate
count-based pruning.'-'
and not containing an '='.
true if there is a command-line
argument specified for the key.
true if the arguments set the specified
flag.
Matrix
interface's documentation.
true if this iterator has more
elements.
true if there are more objects
to return.
true if the next call to Iterators.Buffered.next()
will return a non-null value.
false.
true if calls to next() will
return a value.
true if the underlying iterator has
more elements.
true if there are more elements
left to return.
true if there is another integer in the
iteration.
true if this iterator has another element.
true if the single member has not
already been returned.
true if the arguments have the
specified property defined.
true if the specified matrix has
only zero values on its diagonal.
head.
head element with no attributes.
head element with the specified
attributes.
head element with the specified
attribute and value.
head element with the specified
attributes and values.
head element with the specified
attributes and values.
head element with the specified
attributes and values.
headers attribute.
height attribute.
HeuristicSentenceModel determines sentence
boundaries based on sets of tokens, a pair of flags, and an
overridable method describing boundary conditions.HiddenMarkovModel interface provides a means
for definining the probability estimates and symbol table
underlying a hidden Markov model (HMM).HierarchicalClusterer interface defines a means of
clustering a set of objects into a hierarchy of clusters.HMD value.
HmmCharLmEstimator employs a maximum a posteriori
transition estimator and a bounded character language model
emission estimator.HmmChunker uses a hidden Markov model to perform
chunking over tokenized character sequences.HmmDecoder provides implementations of first-best,
n-best and marginal taggers for hidden Markov models (HMMs).TaggerEvaluator,
MarginalTaggerEvaluator and
NBestTaggerEvaluator instead.TaggerEvaluator,
MarginalTaggerEvaluator and
NBestTaggerEvaluator instead.hr.
hr element with no attributes.
hr element with the specified
attributes.
hr element with the specified
attribute and value.
hr element with the specified
attributes and values.
hr element with the specified
attributes and values.
hr element with the specified
attributes and values.
href attribute.
hreflang attribute.
HSR value.
html.
html element with no attributes.
html element with the specified
attributes.
html element with the specified
attribute and value.
html element with the specified
attributes and values.
html element with the specified
attributes and values.
html element with the specified
attributes and values.
http-equiv attribute.
HyperbolicTangentKernel provides a kernel based on
the hyperbolic tangent of a dot product with fixed linear scaling.i.
i element with no attributes.
i element with the specified
attributes.
i element with the specified
attribute and value.
i element with the specified
attributes and values.
i element with the specified
attributes and values.
i element with the specified
attributes and values.
"I-GENE".
id attribute.
iframe.
iframe element with no attributes.
iframe element with the specified
attributes.
iframe element with the specified
attribute and value.
iframe element with the specified
attributes and values.
iframe element with the specified
attributes and values.
iframe element with the specified
attributes and values.
SAXFilterHandler.mHandler.
img.
img element with no attributes.
img element with the specified
attributes.
img element with the specified
attribute and value.
img element with the specified
attributes and values.
img element with the specified
attributes and values.
img element with the specified
attributes and values.
In-Data-Review value.
In-Process value.
"I_".
"I-".
1.
IndoEuropeanSentenceModel is a heuristic sentence
designed primarily for English.IndoEuropeanTokenCategorizer is a generic token
categorizer for Indo-European languages that is based on character
"shape".IndoEuropeanTokenCategorizer.CATEGORIZER object instead.
IndoEuropeanTokenizerFactory creates tokenizers
with built-in support for alpha-numerics, numbers, and other
common constructs in Indo-European langauges.IndoEuropeanTokenizerFactory.INSTANCE instead.
TokenizedLM.infrequentTermSet(int,int) instead.
Initials element.
input.
input element with no attributes.
input element with the specified
attributes.
input element with the specified
attribute and value.
input element with the specified
attributes and values.
input element with the specified
attributes and values.
input element with the specified
attributes and values.
InputSourceParser is an abstract parser based
on an abstract method for parsing from an input source.ins.
ins element with no attributes.
ins element with the specified
attributes.
ins element with the specified
attribute and value.
ins element with the specified
attributes and values.
ins element with the specified
attributes and values.
ins element with the specified
attributes and values.
ObjectHandler<int[]> instead.InteractionFeatureExtractor produces interaction
features between two feature extractors.*&^INTERCEPT%$^&**.
!java.util.Collections.disjoint(set1,set2).
IntSeqCounter provides counts for sequences of
integers.Investigator element.
IoTagChunkCodec implements a chunk to tag
coder/decoder based on the IO encoding scheme and a
specified tokenizer factory.true if the specified topic is
available in the Reuters collection.
true if the specified tag is the first
token in a chunk.
true if this author is a collective.
true if this list of grants is complete.
true if this reporter is enabled at
the debug level.
true if the specified tagging may be decoded
as a chunking then encoded back to the original tagging accurately.
true if this mapping is empty.
true if this bounded priority
queue has no elements.
true if the queue is empty.
true if the specified level is at least as
severe as the level specified by this reporter.
true if the specified chunking may be encoded
as a tagging then decoded back to the original chunking accurately.
true if this reporter is enabled at
the error level.
true if this reporter is enabled at
the fatal level.
true if the specified token is an
honorific.
true if this reporter is enabled at
the info level.
true if the specified tag is for the
continuation of a chunk.
true if the token has been seen in
training data.
true if this topic is a major
topic for the article.
ismap attribute.
true if the matrix contains only positive
numbers or zeros.
ISOAbbreviation element.
true if the specified tag is for the first
token in a chunk.
true if the specified number is prime.
true if the specified entity type
is a pronominal type.
true if this mention is a pronoun.
true if the specified entity type
is a pronominal type.
true if this mention is a pronoun.
c.size() == 1 instead.
null if one was not provided as part
of the citation.
ISSN element.
ISSNLinking element.
true if this date was provided with year,
season, month and/or day structure.
Issue element.
true if the specified matrix is symmetric.
true if this reporter is enabled at
the trace level.
true if the text of the abstract
has been truncated.
true if this prior is the uniform distribution.
true if the spelling of the authr names
has been validated.
true if the investigator's name has been
validated and false if it has been changed later.
true if the specified character may
appear as part of text content in a MEDLINE record.
true if this reporter is enabled at
the warn level.
Iterators.array(Object[]) instead.Iterators.array(Object[]) instead.
Iterators.arraySlice(Object[],int,int) instead.Iterators.arraySlice(Object[],int,int) instead.
Iterators.Buffered uses a single method to return
objects, buffering the result and returning it as the next element
if it is non-null.Iterators.empty() instead.Iterators.empty() instead.
Iterators.Filter filters the stream of objects
returned by another iterator by subjecting them to an acceptance
test.Iterator.Modifier uses a single abstract method
to operate on the elements returned by an underlying iterator
to return modified objects.Iterators.pair(Object,Object)
instead.Iterators.pair(Object,Object)
instead.
Iterators.PrimitiveInt is an integer iterator that
also allows objects to be accessed as primitive int
values.Iterators.sequence(Iterator,Iterator), Iterators.sequence(Iterator),
or Iterators.sequence(List) instead.Iterators.sequence(Iterator,Iterator) instead.
Iterators.sequence(List) instead.
Iterators.sequence(Iterator) instead.
Iterators.singleton(Object)
instead.Iterators.singleton(Object)
instead.
JaccardDistance class implements a notion of
distance based on token overlap.JaroWinklerDistance class implements the original
Jaro string comparison as well as Winkler's modifications.JointClassification is a conditional classification
derived from a joint probability assignment to each category and
the object being classified.JointClassifier interface specifies a single method for
n-best classification with joint input and category probabilities.JointClassifierEvaluator provides an evaluation harness
for joint probability-based n-best classifiers.Journal element.
JournalIssue element.
kbd.
kbd element with no attributes.
kbd element with the specified
attributes.
kbd element with the specified
attribute and value.
kbd element with the specified
attributes and values.
kbd element with the specified
attributes and values.
kbd element with the specified
attributes and values.
KernelFunction computes real-valued proximities
between vectors.ObjectToDoubleMap.keysOrderedByValueList() instead.
Keyword element.
KeywordList element.
KIE value.
true if the match between mention and
mention chain should be excluded.
true if the specified mention and
mention chain have incompatible genders.
true if the specified mention
and mention chain have incompatible honorifics.
true if there is a killing function that
defeats the match of the mention against the mention chain.
true if there is a killing function that
defeats the match of the mention against the mention chain.
KMeansClusterer provides an implementation of
k-means(++) clustering based on vectors constructed by feature
extractors.KnnClassifier implements k-nearest-neighor
classification based on feature extraction and a vector proximity
or distance.KnownFeatureExtractor restricts a base feature extractor
to features contained in a set provided at construction time.label.
label element with no attributes.
label element with the specified
attributes.
label element with the specified
attribute and value.
label element with the specified
attributes and values.
label element with the specified
attributes and values.
label element with the specified
attributes and values.
label attribute.
lang attribute.
Language element.
LanguageModel provides an estimate of the probability of a
sequence of characters.LanguageModel.Conditional is a language model
that implements conditional estimates of characters given
previous characters.LanguageModel.Dynamic accepts training events in
the form of character slices or sequences.LanguageModel.Process is normalized by length.LanguageModel.Sequence is normalized over all
character sequences.LanguageModel.Tokenized provides a means of
estimating the probability of a sequence of tokens.null if the queue is empty.
LastName element.
LatentDirichletAllocation object represents a latent
Dirichlet allocation (LDA) model.LatentDirichletAllocation.GibbsSample class
encapsulates all of the information related to a single Gibbs
sample for latent Dirichlet allocation (LDA).HmmDecoder.tagMarginal(List) instead.
LeafDendrogram represents a dendrogram consisting
of a single object with link cost of 0.0.true if the specified sequence of tags is a
complete legal tag sequence.
true if the specified sequence of tags
is a legal subsequence of tags.
legend.
legend element with no attributes.
legend element with the specified
attributes.
legend element with the specified
attribute and value.
legend element with the specified
attributes and values.
legend element with the specified
attributes and values.
legend element with the specified
attributes and values.
LengthNormFeatureExtractor converts feature vectors
produced by a contained extractor into unit length vectors.TokenLengthTokenizerFactory or ModifyTokenTokenizerFactory.modify(Tokenizer) instead.ModifyTokenTokenizerFactory.modify(Tokenizer) instead.
li.
li element with no attributes.
li element with the specified
attributes.
li element with the specified
attribute and value.
li element with the specified
attributes and values.
li element with the specified
attributes and values.
li element with the specified
attributes and values.
LineTokenizerFactory treats each line of an input as
a token.LineTokenizerFactory.INSTANCE instead.
link.
link element with no attributes.
link element with the specified
attributes.
link element with the specified
attribute and value.
link element with the specified
attributes and values.
link element with the specified
attributes and values.
link element with the specified
attributes and values.
LinkDendrogram consists of a pair of sub-dendrograms
which are joined at a specified cost.ListCorpus implements a corpus based on a list of
training and test cases.List.toString() instead.
sb.append(ls.toString()).
LMClassifier performs joint probability-based
classification of character sequences into non-overlapping
categories based on language models for each category and a
multivariate distribution over categories.LMClassifier.languageModel(String).
TagWordLattice.log2ConditionalTagList(int) instead.
Model interface which delegates the call to CompiledNGramBoundaryLM.log2Estimate(CharSequence).
Model interface which delegates the call to CompiledNGramProcessLM.log2Estimate(CharSequence).
Model interface which delegates the call to NGramBoundaryLM.log2Estimate(CharSequence).
LogisticRegression instance is a multi-class vector
classifier model generating conditional probability estimates of
categories.LogisticRegressionClassifier provides conditional
probability classifications of input objects using an underlying
logistic regression model and feature extractor.LogLevel is used to indicate a severity level for selecting
which logging messages to report.longdesc attribute.
LowerCaseTokenizerFactory instead.LowerCaseTokenizerFactory or ModifyTokenTokenizerFactory.modify(Tokenizer) instead.
LowerCaseTokenizerFactory or ModifyTokenTokenizerFactory.modify(Tokenizer) instead.
LowerCaseTokenizerFactory filters the tokenizers produced
by a base tokenizer factory to produce lower case output.Locale.English
MajorTopicYN attribute.
java.io.File.
java.io.File.
map.
map element with no attributes.
map element with the specified
attributes.
map element with the specified
attribute and value.
map element with the specified
attributes and values.
map element with the specified
attributes and values.
map element with the specified
attributes and values.
MapDictionary uses an underlying map from phrases to
their set of dictionary entries.MapSymbolTable is a dynamic symbol table based on a
pair of underlying maps.LatentDirichletAllocation.bayesTopicEstimate(int[],int,int,int,Random)
instead.
MarginalTagger<E> interface is for objects that tag a
list of tokens with marginal per-tag and transition probabilities.MarginalTaggerEvaluator evaluates marginal taggers either
directly or by adding their outputs.Matcher.
true if the specified mention matches
the specified mention chain.
true if the mention has the type
that was specified in the constructor.
true if the normal phrase of the mention
is equal to the normal phrase of a mention in the mention chain.
true if the normal tokens in the mention
are within a threshold edit distance of the normal tokens in
one of the mentions in the chain.
true if the mention's normal phrase has a
synonym that is the normal phrase of one of the chain's mentions.
Matrices class contains static utility methods
for various matrix properties and operations.Matrix represents a 2-dimensional matrix.Matcher.MAX_SEMANTIC_SCORE +
Matcher.MAX_DISTANCE_SCORE4.
maxlength attribute.
Double.NaN if the feature is not known.
media attribute.
MedlineCitation element.
MedlineCitationSet element.
MedlineDate element.
MedlineJournalInfo element.
MedlinePgn element.
MedlineTA element.
MEDLINE value (for citation status).
MedlineHandler interface specifies a single method
that applies to a MEDLINE citation.MedlineSentenceModel is a heuristic sentence model
designed for operating over biomedical research abstracts as found
in MEDLINE.null handler.
Mention represents a single mention of
a given phrase in context.MentionChain represents a set of mentions that have
been resolved as coreferent in that they refer to the same
underlying entity.MentionFactory is responsible for creating
and merging mentions and mention chains.AbstractMentionChain.entityType() or AbstractMentionChain.setEntityType(String) instead.
menu.
menu element with no attributes.
menu element with the specified
attributes.
menu element with the specified
attribute and value.
menu element with the specified
attributes and values.
menu element with the specified
attributes and values.
menu element with the specified
attributes and values.
MeshHeading element.
MeshHeadingList element.
meta.
meta element with no attributes.
meta element with the specified
attributes.
meta element with the specified
attribute and value.
meta element with the specified
attributes and values.
meta element with the specified
attributes and values.
meta element with the specified
attributes and values.
method attribute.
AbstractMentionChain.gender() or AbstractMentionChain.setGender(String) instead.
AbstractMentionChain.honorifics() or AbstractMentionChain.addHonorific(String) instead.
MiddleName element.
MinkowskiDistance class implements Minkowski
distance of a fixed order between vectors.MinMaxHeap provides a heap-like data structure that
provides fast access to both the minimum and maximum elements of
the heap.0.
true if this evaluation involved conditional
classifications that did not score every category.
true if this evaluation involved ranked
classifications that did not rank every category.
true if this evaluation involved ranked
classifications that did not score every category.
Model represents a generic interface for
classes that estimate probabilities of objects.ModifiedFeatureExtractor allows feature values to be
modified in a feature-specific fashion.ModifiedTokenizerFactory is an abstract tokenizer factory
that modifies a tokenizer returned by a base tokenizer factory.null to remove it.
null otherwise.
ModifyTokenTokenizerFactory
adapts token and whitespace modifiers to modify tokenizer
factories.Month element.
FilterTokenizer.baseTokenizer() for reads
and create a new instance of FilterTokenizer itself for
different values.
TokenizedDistance.tokenizerFactory() instead.
MultinomialDistribution results from drawing a fixed
number of samples from a multivariate distribution.multiple attribute.
MultiTrieReader merges two trie readers, providing
output that is the result of adding the counts from the two readers.MultivariateConstant provides a multinomial
distribution with constant probabilities and labels.MultivariateDistribution implements a discrete
distribution over a finite set of outcomes numbered consecutively
from zero.MultivariateEstimator provides a maximum likelihood
estimator of a multivariate distribution based on training samples.NaiveBayesClassifier provides a trainable naive Bayes
text classifier, with tokens as features.name attribute.
NameId element.
NameOfSubstance element.
NameQualifier element.
XMLReader to
handle namespaces.
NASA value.
HmmDecoder.tagNBest(List,int) instead.
HmmDecoder.tagNBest(List,int) instead.
NBestChunker is a chunker that is able to return
results iterating over scored chunkings or scored chunks in order
of decreasing likelihood.HmmDecoder.tagNBestConditional(List,int) instead.
BoundedPriorityQueue or ShortPriorityQueue
instead.NBestTagger<E> interface for objects that tag a list of
objects with multiple tagged results.NBestTaggerEvaluator provides an evaluation
framework for n-best taggers.Class.forName(className).getConstructor(new Class[0]).newInstance(new Object[0]) instead.
args to argClasses using args[i].getClass(),
then call Class.forName(className).getConstructor(argClasses).newInstace(args) instead.
argClassNames to argClasses
classes using Class.forName(argClassNames[i]), then use
Class.forName(className).getConstructor(argClasses).newInstace(args) instead.
Class.forName(className).getConstructor(argClasses).newInstance(args) instead.
TokenizedLM.newTermSet(int,int,int,LanguageModel.Tokenized)
instead.
Iterators.Modifier.modify(Object).
StopFilterTokenizer.stop(String), or null if there are no
more underlying tokens.
null if
there are no more tokens.
Strings.SINGLE_SPACE_STRING
or the empty string Strings.EMPTY_STRING.
NGramBoundaryLM provides a dynamic sequence
language model for which training, estimation and pruning may be
interleaved.NGramProcessLM provides a dynamic conditional
process language model process for which training, estimation, and
pruning may be interleaved.NGramTokenizerFactory creates n-gram tokenizers
of a specified minimum and maximun length.NlmDcmsID element.
NlmUniqueID element.
NLM value.
N value.
true if there are no elements in the stack.
noframes.
noframes element with no attributes.
noframes element with the specified
attributes.
noframes element with the specified
attribute and value.
noframes element with the specified
attributes and values.
noframes element with the specified
attributes and values.
noframes element with the specified
attributes and values.
nohref attribute.
WhitespaceNormTokenizerFactory instead.WhitespaceNormTokenizerFactory or
ModifyTokenTokenizerFactory.modify(Tokenizer)
instead.
noscript.
noscript element with no attributes.
noscript element with the specified
attributes.
noscript element with the specified
attribute and value.
noscript element with the specified
attributes and values.
noscript element with the specified
attributes and values.
noscript element with the specified
attributes and values.
NOTNLM value.
SAXFilterHandler.mHandler.
Note element.
NumberOfReferences element.
object.
object element with no attributes.
object element with the specified
attributes.
object element with the specified
attribute and value.
object element with the specified
attributes and values.
object element with the specified
attributes and values.
object element with the specified
attributes and values.
ObjectHandler interface specifies a handler
with a single method that takes a single argument of the
type of the generic paramter.ObjectToCounterMap maintains a mapping from objects
to integer counters, which may be incremented or set.ObjectToDoubleMap maintains a mapping from
objects to double-valued counters, which may be incremented or set.ObjectToSet provides a Map from
arbitrary objects to objects of class Set.true if the specified element may be added to
the queue.
OfficialDateYN attribute.
ol.
ol element with no attributes.
ol element with the specified
attributes.
ol element with the specified
attribute and value.
ol element with the specified
attributes and values.
ol element with the specified
attributes and values.
ol element with the specified
attributes and values.
OLDMEDLINE value (for citation status).
TokenizedLM.oldTermSet(int,int,int,LanguageModel.Tokenized) instead.
onblur attribute.
onchange attribute.
onclick attribute.
ondblclick attribute.
Integer with value 1.
onfocus attribute.
onkeydown attribute.
onkeypress attribute.
onkeyup attribute.
OnlineNormalEstimator provides an object that estimates
means, variances, and standard deviations for a stream of numbers
presented one at a time.onload attribute.
onmousedown attribute.
onmousemove attribute.
onmouseout attribute.
onmouseover attribute.
onmouseup attribute.
onreset attribute.
onselect attribute.
onsubmit attribute.
onunload attribute.
optgroup.
optgroup element with no attributes.
optgroup element with the specified
attributes.
optgroup element with the specified
attribute and value.
optgroup element with the specified
attributes and values.
optgroup element with the specified
attributes and values.
optgroup element with the specified
attributes and values.
option.
option element with no attributes.
option element with the specified
attributes.
option element with the specified
attribute and value.
option element with the specified
attributes and values.
option element with the specified
attributes and values.
option element with the specified
attributes and values.
OtherAbstract element.
OtherID element.
OtherInformation element.
"O".
"O" (the letter O).
true if the chunks overlap at least one
character position.
Owner attribute.
p.
p element with no attributes.
p element with the specified
attributes.
p element with the specified
attribute and value.
p element with the specified
attributes and values.
p element with the specified
attributes and values.
p element with the specified
attributes and values.
Strings.DEFAULT_SEPARATOR_CHAR.
Strings.DEFAULT_SEPARATOR_CHAR to the specified string buffer.
null
if there is no page numbering for this article if it is electronic only.
Pair class represents an immutable pair of objects
of heterogeneous type.param.
param element with no attributes.
param element with the specified
attributes.
param element with the specified
attribute and value.
param element with the specified
attributes and values.
param element with the specified
attributes and values.
param element with the specified
attributes and values.
null if this is a top-level
dendrogram.
setHandler(MedlineHandler) followed
by parse(InputSource).
Parser abstract class provides methods for parsing
content from an input source or character sequence and passing
extracted events to a content handler.null handler.
SvdMatrix.partialSvd(int[][],double[][],int,double,double,double,double,Reporter,double,int,int)
instead.
SvdMatrix.partialSvd(int[][],double[][],int,double,double,double,double,Random,Reporter,double,int,int) instead.
SvdMatrix.partialSvd(int[][],double[][],int,double,double,double,double,Random,Reporter,double,int,int) instead.
null if the queue is empty.
null
if the queue is empty.
null if the queue is empty.
null if the queue is empty.
null if the queue is empty.
null
if it is empty.
null
if it is empty.
PerceptronClassifier implements a binary classifier
based on an averaged kernel-based perceptron.PerceptronClassifier.PerceptronClassifier(Corpus,FeatureExtractor,KernelFunction,String,int,String,String) instead.
PerceptronClassifier.PerceptronClassifier(Corpus,FeatureExtractor,KernelFunction,String,int,String,String) instead.
PersonalNameSubject element.
MarginalTaggerEvaluator.perTokenEval() instead.
AbstractDictionary.phraseEntryList(String) instead.
Dictionary.phraseEntryList(String) instead.
PIP value.
PMID element.
PoissonConstant implements a Poisson
distribution with a fixed mean.PoissonDistribution abstract class is used for
calculating Poisson distributions.PoissonEstimator implements the maximum likelihood
Poisson distribution given training events.null if it is empty.
null if the queue is empty.
PolynomialKernel provides a dot product over a fixed
degree polynomial basis expansion of a vector.BoundedPriorityQueue.poll() instead.
null if the queue is empty.
null if the heap is empty.
null if the heap is empty.
PorterStemmerTokenizerFactory.stem(String) instead.PorterStemmerTokenizerFactory instead.PorterStemmerTokenizerFactory applies Porter's stemmer
to the tokenizers produced by a base tokenizer factory.true if the specified start index can
be a sentence start in the specified array of tokens and
whitespaces running up to the end token.
true if the specified start index can
be a sentence start in the specified array of tokens and
whitespaces running up to the end token.
PotentialScaleReduction class provides an online
computationa of Rhat, the potential scale reduction statistic for
measuring mixing and convergence of multiple Markov chain Monte
Carlo (MCMC) samplers.pre.
pre element with no attributes.
pre element with the specified
attributes.
pre element with the specified
attribute and value.
pre element with the specified
attributes and values.