# All Classes and Interfaces

Class
Description
BasicContextGenerator
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:
BinaryGISModelReader
A `GISModelReader` that reads models from a binary format.
BinaryGISModelWriter
A `GISModelWriter` that writes models in a binary format.
BinaryQNModelReader
A `QNModelReader` that reads models from a binary format.
BinaryQNModelWriter
A `QNModelWriter` that writes models in a binary format.
ContextGenerator<T>
Represents a generator of contexts for maxent decisions.
DataStream
An interface for objects which can deliver a stream of training data to be supplied to an EventStream.
Function
Interface for a function.
GISModel
A maximum entropy model which has been trained using the Generalized Iterative Scaling (GIS) procedure.
GISModelReader
The base class for readers of `GIS models`.
GISModelWriter
The base class for writers of `GIS models`.
GISTrainer
An implementation of Generalized Iterative Scaling (GIS).
LineSearch
Performs line search to find a minimum.
LineSearch.LineSearchResult
Represents a `LineSearch` result encapsulating the relevant data at a point in time during computation.
LogLikelihoodThresholdBreached
A `StopCriteria` implementation to identify whether the difference between the log likelihood of current and previous iteration is under the defined threshold.
NegLogLikelihood
Evaluates negative log-likelihood and its gradient from `DataIndexer`.
ParallelNegLogLikelihood
Evaluates `negative log-likelihood` and its gradient in parallel.
QNMinimizer
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.Evaluator
Evaluate the quality of training parameters.
QNMinimizer.L2RegFunction
L2-regularized objective `Function`.
QNModel
A `maximum entropy model` which has been trained via the L-BFGS algorithm , which belongs to the group of Quasi Newton (QN) algorithms.
QNModelReader
The base class for readers of `QN models`.
QNModelWriter
The base class for writers of `models`.
QNTrainer
A Maxent model `trainer` using the L-BFGS algorithm.
RealBasicEventStream
Class for real-valued `events` as an `event stream`. .
URLInputStreamFactory