# Package opennlp.tools.ml.model

Package related to ML models and feature selection techniques.

- Interface Summary
  Interface | Description
  --- | ---
  DataIndexer | Represents an indexer which compresses events in memory and performs feature selection.
  DataReader | Describes generic ways to read data from a `DataInputStream`.
  MaxentModel | Interface for maximum entropy models.
  Prior | This interface allows one to implement a prior distribution for use in maximum entropy model training.
  SequenceClassificationModel<T> | A classification model that can label an input `Sequence`.
  SequenceStream<S> | Interface for streams of `sequences` used to train sequence models.

- Class Summary
  Class | Description
  --- | ---
  AbstractDataIndexer | Abstract `DataIndexer` implementation for collecting event and context counts used in training.
  AbstractModel | A basic `MaxentModel` implementation.
  AbstractModelReader | An abstract, basic implementation of a model reader.
  AbstractModelWriter | An abstract, basic implementation of a model writer.
  BinaryFileDataReader | A `DataReader` that reads files from a binary format.
  ComparableEvent | A maxent event representation which we can use to sort based on the predicates indexes contained in the events.
  ComparablePredicate | A maxent predicate representation which we can use to sort based on the outcomes.
  Context | Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
  DataIndexerFactory | A factory that produces `DataIndexer` instances.
  DynamicEvalParameters |
  EvalParameters | This class encapsulates the variables used in producing probabilities from a model and facilitates passing these variables to the eval method.
  Event | The context of a decision point during training.
  FileEventStream | Class for using a file of `events` as an `event stream`.
  GenericModelReader | An generic `AbstractModelReader` implementation.
  GenericModelWriter | An generic `AbstractModelWriter` implementation.
  HashSumEventStream | A hash sum based `AbstractObjectStream` implementation.
  ModelParameterChunker | A helper class that handles Strings with more than 64k (65535 bytes) in length.
  MutableContext | An extension of `Context` used to store parameters or expected values associated with this context which can be updated or assigned.
  ObjectDataReader | A `DataReader` implementation based on `ObjectInputStream`.
  OnePassDataIndexer | A `DataIndexer` for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates.
  OnePassRealValueDataIndexer | A `DataIndexer` for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates and maintains event values.
  PlainTextFileDataReader | A generic `DataReader` implementation for plain text files.
  RealValueFileEventStream | Class for using a file of real-valued `events` as an `event stream`.
  Sequence<T> | Class which models a sequence.
  SequenceStreamEventStream | Class which turns a `SequenceStream` into an event stream.
  TwoPassDataIndexer | Collecting event and context counts by making two passes over the events.
  UniformPrior | Provide a maximum entropy model with a uniform `Prior`.

- Enum Summary
  Enum | Description
  --- | ---
  AbstractModel.ModelType |