# Index

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<TrainingParameters>) - Method in class opennlp.tools.ml.maxent.GISTrainer
doTrain(DataIndexer<TrainingParameters>) - 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<String, String>) - Method in class opennlp.tools.ml.maxent.GISTrainer
init(TrainingParameters, Map<String, String>) - 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<TrainingParameters>) - 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<TrainingParameters>, 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<String>) - 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<TrainingParameters>) - Method in class opennlp.tools.ml.maxent.GISTrainer
  Trains a model using the GIS algorithm.
trainModel(int, DataIndexer<TrainingParameters>) - Method in class opennlp.tools.ml.maxent.quasinewton.QNTrainer
  Trains a `model` using the QN algorithm.
trainModel(int, DataIndexer<TrainingParameters>, int) - Method in class opennlp.tools.ml.maxent.GISTrainer
  Trains a model using the GIS algorithm.
trainModel(int, DataIndexer<TrainingParameters>, Prior, int) - Method in class opennlp.tools.ml.maxent.GISTrainer
  Trains a model using the GIS algorithm.
trainModel(ObjectStream<Event>) - Method in class opennlp.tools.ml.maxent.GISTrainer
  Trains a model using the GIS algorithm, assuming 100 iterations and no cutoff.
trainModel(ObjectStream<Event>, 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