Index (Apache OpenNLP :: Core :: ML :: Maximum Entropy 3.0.0-M2 API)

B C D E F G H I L M N O P Q R S T U V W
All Classes and Interfaces|All Packages|Constant Field Values

B

BasicContextGenerator - Class in opennlp.tools.ml.maxent: A ContextGenerator implementation for maxent decisions, assuming that the input given to the BasicContextGenerator.getContext(String) method is a String containing contextual predicates separated by spaces, for instance:
BasicContextGenerator() - Constructor for class opennlp.tools.ml.maxent.BasicContextGenerator
BasicContextGenerator(String) - Constructor for class opennlp.tools.ml.maxent.BasicContextGenerator: Initializes a BasicContextGenerator with a different separator char.
BinaryGISModelReader - Class in opennlp.tools.ml.maxent.io: A GISModelReader that reads models from a binary format.
BinaryGISModelReader(DataInputStream) - Constructor for class opennlp.tools.ml.maxent.io.BinaryGISModelReader: Instantiates BinaryGISModelReader via a DataInputStream containing the model contents.
BinaryGISModelWriter - Class in opennlp.tools.ml.maxent.io: A GISModelWriter that writes models in a binary format.
BinaryGISModelWriter(AbstractModel, DataOutputStream) - Constructor for class opennlp.tools.ml.maxent.io.BinaryGISModelWriter: Instantiates BinaryGISModelWriter via an GIS model and a DataOutputStream.
BinaryGISModelWriter(AbstractModel, File) - Constructor for class opennlp.tools.ml.maxent.io.BinaryGISModelWriter: Instantiates BinaryGISModelWriter via an GIS model and a File.
BinaryQNModelReader - Class in opennlp.tools.ml.maxent.io: A QNModelReader that reads models from a binary format.
BinaryQNModelReader(DataInputStream) - Constructor for class opennlp.tools.ml.maxent.io.BinaryQNModelReader: Instantiates BinaryQNModelReader via a DataInputStream containing the model contents.
BinaryQNModelWriter - Class in opennlp.tools.ml.maxent.io: A QNModelWriter that writes models in a binary format.
BinaryQNModelWriter(AbstractModel, DataOutputStream) - Constructor for class opennlp.tools.ml.maxent.io.BinaryQNModelWriter: Instantiates BinaryQNModelWriter via an QN model and a DataOutputStream.
BinaryQNModelWriter(AbstractModel, File) - Constructor for class opennlp.tools.ml.maxent.io.BinaryQNModelWriter: Instantiates BinaryQNModelWriter via an QN model and a File.

C

checkModelType() - Method in class opennlp.tools.ml.maxent.io.GISModelReader
checkModelType() - Method in class opennlp.tools.ml.maxent.io.QNModelReader
close() - Method in class opennlp.tools.ml.maxent.io.BinaryGISModelWriter
close() - Method in class opennlp.tools.ml.maxent.io.BinaryQNModelWriter
close() - Method in class opennlp.tools.ml.maxent.RealBasicEventStream
constructModel() - Method in class opennlp.tools.ml.maxent.io.GISModelReader: Retrieves a model from disk.
constructModel() - Method in class opennlp.tools.ml.maxent.io.QNModelReader: Retrieves a model from disk.
ContextGenerator<T> - Interface in opennlp.tools.ml.maxent: Represents a generator of contexts for maxent decisions.
CONVERGE_TOLERANCE - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer
createInputStream() - Method in class opennlp.tools.ml.maxent.URLInputStreamFactory

D

DataStream - Interface in opennlp.tools.ml.maxent: An interface for objects which can deliver a stream of training data to be supplied to an EventStream.
doConstrainedLineSearch(Function, double[], LineSearch.LineSearchResult, double, double) - Static method in class opennlp.tools.ml.maxent.quasinewton.LineSearch: Conducts a constrained line search (see section 3.2 in the paper "Scalable Training of L1-Regularized Log-Linear Models", Andrew et al. 2007)
doLineSearch(Function, double[], LineSearch.LineSearchResult, double) - Static method in class opennlp.tools.ml.maxent.quasinewton.LineSearch: Conducts a backtracking line search.
doTrain(DataIndexer) - Method in class opennlp.tools.ml.maxent.GISTrainer
doTrain(DataIndexer) - Method in class opennlp.tools.ml.maxent.quasinewton.QNTrainer

E

equals(Object) - Method in class opennlp.tools.ml.maxent.GISModel
eval(int[], double[], EvalParameters) - Static method in class opennlp.tools.ml.maxent.GISModel: Evaluates a context and return an array of the likelihood of each outcome given the specified context and the specified parameters.
eval(String[]) - Method in class opennlp.tools.ml.maxent.GISModel: Evaluates a context and return an array of the likelihood of each outcome given that context.
eval(String[]) - Method in class opennlp.tools.ml.maxent.quasinewton.QNModel
eval(String[], double[]) - Method in class opennlp.tools.ml.maxent.GISModel
eval(String[], double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.QNModel
eval(String[], float[]) - Method in class opennlp.tools.ml.maxent.GISModel
eval(String[], float[]) - Method in class opennlp.tools.ml.maxent.quasinewton.QNModel
eval(String[], float[], double[]) - Method in class opennlp.tools.ml.maxent.GISModel: Evaluates a context and return an array of the likelihood of each outcome given that context.
evaluate(double[]) - Method in interface opennlp.tools.ml.maxent.quasinewton.QNMinimizer.Evaluator: Measure quality of the training parameters.

F

Function - Interface in opennlp.tools.ml.maxent.quasinewton: Interface for a function.

G

getContext(String) - Method in class opennlp.tools.ml.maxent.BasicContextGenerator
getContext(T) - Method in interface opennlp.tools.ml.maxent.ContextGenerator: Builds up the list of contextual predicates given an object.
getCurrPoint() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getDimension() - Method in interface opennlp.tools.ml.maxent.quasinewton.Function
getDimension() - Method in class opennlp.tools.ml.maxent.quasinewton.NegLogLikelihood
getDimension() - Method in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer.L2RegFunction
getEvaluator() - Method in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer
getFctEvalCount() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getFuncChangeRate() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getGradAtCurr() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getGradAtNext() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getInitialObject(double, double[], double[]) - Static method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Initial linear search object for L1-regularization.
getInitialObject(double, double[], double[], double[], double[], int) - Static method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Initial linear search object for L1-regularization.
getInitialObjectForL1(double, double[], double[], double[]) - Static method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Initial linear search object for L1-regularization.
getInitialPoint() - Method in class opennlp.tools.ml.maxent.quasinewton.NegLogLikelihood
getMessageIfSatisfied() - Method in class opennlp.tools.monitoring.LogLikelihoodThresholdBreached
getNextPoint() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getNumOutcomes() - Method in class opennlp.tools.ml.maxent.quasinewton.QNModel
getPseudoGradAtNext() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getSignVector() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getStepSize() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getValueAtCurr() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
getValueAtNext() - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
GISModel - Class in opennlp.tools.ml.maxent: A maximum entropy model which has been trained using the Generalized Iterative Scaling (GIS) procedure.
GISModel(Context[], String[], String[]) - Constructor for class opennlp.tools.ml.maxent.GISModel: Initializes a GISModel with the specified parameters, outcome names, and predicate/feature labels.
GISModel(Context[], String[], String[], Prior) - Constructor for class opennlp.tools.ml.maxent.GISModel: Initializes a GISModel with the specified parameters, outcome names, and predicate/feature labels.
GISModelReader - Class in opennlp.tools.ml.maxent.io: The base class for readers of GIS models.
GISModelReader(File) - Constructor for class opennlp.tools.ml.maxent.io.GISModelReader: Initializes a GISModelReader via a File.
GISModelReader(DataReader) - Constructor for class opennlp.tools.ml.maxent.io.GISModelReader: Initializes a GISModelReader via a DataReader.
GISModelWriter - Class in opennlp.tools.ml.maxent.io: The base class for writers of GIS models.
GISModelWriter(AbstractModel) - Constructor for class opennlp.tools.ml.maxent.io.GISModelWriter: Initializes a GISModelWriter for a GIS model.
GISTrainer - Class in opennlp.tools.ml.maxent: An implementation of Generalized Iterative Scaling (GIS).
GISTrainer() - Constructor for class opennlp.tools.ml.maxent.GISTrainer: Initializes a GISTrainer.
gradientAt(double[]) - Method in interface opennlp.tools.ml.maxent.quasinewton.Function: Computes the gradient for x.
gradientAt(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.NegLogLikelihood: Computes the gradient.
gradientAt(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.ParallelNegLogLikelihood: Computes the gradient for x.
gradientAt(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer.L2RegFunction

H

hashCode() - Method in class opennlp.tools.ml.maxent.GISModel
hasNext() - Method in interface opennlp.tools.ml.maxent.DataStream: Test whether there are any events remaining in this DataStream.

I

init(TrainingParameters, Map) - Method in class opennlp.tools.ml.maxent.GISTrainer
init(TrainingParameters, Map) - Method in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
INITIAL_STEP_SIZE - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: The initial step size: 1.0.
isSortAndMerge() - Method in class opennlp.tools.ml.maxent.GISTrainer
isSortAndMerge() - Method in class opennlp.tools.ml.maxent.quasinewton.QNTrainer

L

L1COST_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: The default L1-cost value is 0.0d.
L1COST_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer: The default L1-cost value is 0.1d.
L1COST_PARAM - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
L2COST_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: The default L2-cost value is 0.0d.
L2COST_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer: The default L2-cost value is 0.1d.
L2COST_PARAM - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
L2RegFunction(Function, double) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNMinimizer.L2RegFunction
LineSearch - Class in opennlp.tools.ml.maxent.quasinewton: Performs line search to find a minimum.
LineSearch() - Constructor for class opennlp.tools.ml.maxent.quasinewton.LineSearch
LineSearch.LineSearchResult - Class in opennlp.tools.ml.maxent.quasinewton: Represents a LineSearch result encapsulating the relevant data at a point in time during computation.
LineSearchResult(double, double, double, double[], double[], double[], double[], double[], double[], int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Initializes a LineSearch.LineSearchResult object with the specified parameters.
LineSearchResult(double, double, double, double[], double[], double[], double[], int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Initializes a LineSearch.LineSearchResult object with the specified parameters.
LOG_LIKELIHOOD_THRESHOLD_DEFAULT - Static variable in class opennlp.tools.ml.maxent.GISTrainer
LOG_LIKELIHOOD_THRESHOLD_PARAM - Static variable in class opennlp.tools.ml.maxent.GISTrainer
LogLikelihoodThresholdBreached - Class in opennlp.tools.monitoring: A StopCriteria implementation to identify whether the difference between the log likelihood of current and previous iteration is under the defined threshold.
LogLikelihoodThresholdBreached(Parameters) - Constructor for class opennlp.tools.monitoring.LogLikelihoodThresholdBreached

M

M_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: The default number of Hessian updates to store is 15.
M_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer: The default number of Hessian updates to store is 15.
M_PARAM - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
MAX_FCT_EVAL_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: The default maximum number of function evaluations is 30,000.
MAX_FCT_EVAL_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer: The default maximum number of function evaluations is 30,000.
MAX_FCT_EVAL_PARAM - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
MAXENT_QN_VALUE - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
MIN_STEP_SIZE - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: The minimum step size: 1e-10.
minimize(Function) - Method in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: Finds the parameters that minimize the objective function.

N

NegLogLikelihood - Class in opennlp.tools.ml.maxent.quasinewton: Evaluates negative log-likelihood and its gradient from DataIndexer.
NegLogLikelihood(DataIndexer) - Constructor for class opennlp.tools.ml.maxent.quasinewton.NegLogLikelihood
nextToken() - Method in interface opennlp.tools.ml.maxent.DataStream: Returns the next slice of data held in this DataStream.
NUM_ITERATIONS_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: By default the number of iterations is 100.

O

opennlp.tools.ml.maxent - package opennlp.tools.ml.maxent: Provides main functionality of the maxent package including data structures and algorithms for parameter estimation.
opennlp.tools.ml.maxent.io - package opennlp.tools.ml.maxent.io: Provides the I/O functionality of the maxent package including reading and writing models in several formats.
opennlp.tools.ml.maxent.quasinewton - package opennlp.tools.ml.maxent.quasinewton
opennlp.tools.monitoring - package opennlp.tools.monitoring

P

ParallelNegLogLikelihood - Class in opennlp.tools.ml.maxent.quasinewton: Evaluates negative log-likelihood and its gradient in parallel.
ParallelNegLogLikelihood(DataIndexer, int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.ParallelNegLogLikelihood
persist() - Method in class opennlp.tools.ml.maxent.io.GISModelWriter: Writes the GIS model, using the AbstractModelWriter.writeUTF(String), AbstractModelWriter.writeDouble(double), or AbstractModelWriter.writeInt(int)} methods implemented by extending classes.
persist() - Method in class opennlp.tools.ml.maxent.io.QNModelWriter: Writes the QN model, using the AbstractModelWriter.writeUTF(String), AbstractModelWriter.writeDouble(double), or AbstractModelWriter.writeInt(int)} methods implemented by extending classes.

Q

QNMinimizer - Class in opennlp.tools.ml.maxent.quasinewton: Implementation of the Limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) which supports L1-, L2-regularization and Elastic Net for solving convex optimization problems.
QNMinimizer() - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: Initializes a QNMinimizer with default parameters (see: QNMinimizer.L1COST_DEFAULT and QNMinimizer.L2COST_DEFAULT).
QNMinimizer(double, double) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: Initializes a QNMinimizer.
QNMinimizer(double, double, int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: Initializes a QNMinimizer with L1 and L2 parameters.
QNMinimizer(double, double, int, int, int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNMinimizer: Initializes a QNMinimizer.
QNMinimizer.Evaluator - Interface in opennlp.tools.ml.maxent.quasinewton: Evaluate the quality of training parameters.
QNMinimizer.L2RegFunction - Class in opennlp.tools.ml.maxent.quasinewton: L2-regularized objective Function.
QNModel - Class in opennlp.tools.ml.maxent.quasinewton: A maximum entropy model which has been trained via the L-BFGS algorithm , which belongs to the group of Quasi Newton (QN) algorithms.
QNModel(Context[], String[], String[]) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNModel: Initializes a QNModel with the specified parameters, predicate/feature labels, and outcome names.
QNModelReader - Class in opennlp.tools.ml.maxent.io: The base class for readers of QN models.
QNModelReader(File) - Constructor for class opennlp.tools.ml.maxent.io.QNModelReader: Initializes a QNModelReader via a File.
QNModelReader(DataReader) - Constructor for class opennlp.tools.ml.maxent.io.QNModelReader: Initializes a QNModelReader via a DataReader.
QNModelWriter - Class in opennlp.tools.ml.maxent.io: The base class for writers of models.
QNModelWriter(AbstractModel) - Constructor for class opennlp.tools.ml.maxent.io.QNModelWriter
QNTrainer - Class in opennlp.tools.ml.maxent.quasinewton: A Maxent model trainer using the L-BFGS algorithm.
QNTrainer() - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNTrainer: Initializes a QNTrainer.
QNTrainer(int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNTrainer: Initializes a QNTrainer with the specified parameter m.
QNTrainer(int, int) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNTrainer: Initializes a QNTrainer with the specified parameters.
QNTrainer(TrainingParameters) - Constructor for class opennlp.tools.ml.maxent.quasinewton.QNTrainer: Initializes a QNTrainer with the specified parameters.

R

read() - Method in class opennlp.tools.ml.maxent.RealBasicEventStream
RealBasicEventStream - Class in opennlp.tools.ml.maxent: Class for real-valued events as an event stream. .
RealBasicEventStream(ObjectStream) - Constructor for class opennlp.tools.ml.maxent.RealBasicEventStream
REL_GRAD_NORM_TOL - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer
reset() - Method in class opennlp.tools.ml.maxent.RealBasicEventStream

S

setAll(double, double, double, double[], double[], double[], double[], double[], double[], int) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Updates line search elements.
setAll(double, double, double, double[], double[], double[], double[], int) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult: Updates line search elements.
setCurrPoint(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setEvaluator(QNMinimizer.Evaluator) - Method in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer
setFctEvalCount(int) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setGaussianSigma(double) - Method in class opennlp.tools.ml.maxent.GISTrainer: Sets whether this trainer will use smoothing while training the model.
setGradAtCurr(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setGradAtNext(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setNextPoint(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setPseudoGradAtNext(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setSignVector(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setSmoothing(boolean) - Method in class opennlp.tools.ml.maxent.GISTrainer: Sets whether this trainer will use smoothing while training the model.
setSmoothingObservation(double) - Method in class opennlp.tools.ml.maxent.GISTrainer: Sets whether this trainer will use smoothing while training the model.
setStepSize(double) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setValueAtCurr(double) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
setValueAtNext(double) - Method in class opennlp.tools.ml.maxent.quasinewton.LineSearch.LineSearchResult
STOP - Static variable in class opennlp.tools.monitoring.LogLikelihoodThresholdBreached

T

test(Double) - Method in class opennlp.tools.monitoring.LogLikelihoodThresholdBreached
THREADS_DEFAULT - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
THREADS_PARAM - Static variable in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
trainModel(int, DataIndexer) - Method in class opennlp.tools.ml.maxent.GISTrainer: Trains a model using the GIS algorithm.
trainModel(int, DataIndexer) - Method in class opennlp.tools.ml.maxent.quasinewton.QNTrainer: Trains a model using the QN algorithm.
trainModel(int, DataIndexer, int) - Method in class opennlp.tools.ml.maxent.GISTrainer: Trains a model using the GIS algorithm.
trainModel(int, DataIndexer, Prior, int) - Method in class opennlp.tools.ml.maxent.GISTrainer: Trains a model using the GIS algorithm.
trainModel(ObjectStream) - Method in class opennlp.tools.ml.maxent.GISTrainer: Trains a model using the GIS algorithm, assuming 100 iterations and no cutoff.
trainModel(ObjectStream, int, int) - Method in class opennlp.tools.ml.maxent.GISTrainer: Trains a GIS model on the event in the specified event stream, using the specified number of iterations and the specified count cutoff.

U

URLInputStreamFactory - Class in opennlp.tools.ml.maxent
URLInputStreamFactory(URL) - Constructor for class opennlp.tools.ml.maxent.URLInputStreamFactory

V

validate() - Method in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
valueAt(double[]) - Method in interface opennlp.tools.ml.maxent.quasinewton.Function: Computes the function value for x.
valueAt(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.NegLogLikelihood: Computes the negative log-likelihood.
valueAt(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.ParallelNegLogLikelihood: Computes the function value for x.
valueAt(double[]) - Method in class opennlp.tools.ml.maxent.quasinewton.QNMinimizer.L2RegFunction

W

writeDouble(double) - Method in class opennlp.tools.ml.maxent.io.BinaryGISModelWriter
writeDouble(double) - Method in class opennlp.tools.ml.maxent.io.BinaryQNModelWriter
writeInt(int) - Method in class opennlp.tools.ml.maxent.io.BinaryGISModelWriter
writeInt(int) - Method in class opennlp.tools.ml.maxent.io.BinaryQNModelWriter
writeUTF(String) - Method in class opennlp.tools.ml.maxent.io.BinaryGISModelWriter
writeUTF(String) - Method in class opennlp.tools.ml.maxent.io.BinaryQNModelWriter

B C D E F G H I L M N O P Q R S T U V W
All Classes and Interfaces|All Packages|Constant Field Values