# Uses of Package
opennlp.tools.ml.model

Packages that use opennlp.tools.ml.model
Package
Description
opennlp.tools.chunker
Package related to finding non-recursive syntactic annotation such as noun phrase chunks.
opennlp.tools.doccat
Package for classifying a document into a category.
opennlp.tools.langdetect
Package related to predicting languages from samples of text.
opennlp.tools.lemmatizer
Package related to the lemmatizer functionality.
opennlp.tools.ml
Package related to Machine Learning (ML) features of OpenNLP, the related ML models, and trainers.
opennlp.tools.ml.maxent
Package related to ML by means of the Maximum Entropy (ME) algorithm.
opennlp.tools.ml.maxent.io
Package related to the I/O functionality of the maxent package including reading and writing models in several formats.
opennlp.tools.ml.maxent.quasinewton
Package related to ML by means of the Quasi Newton (QN) algorithm.
opennlp.tools.ml.model
Package related to ML models and feature selection techniques.
opennlp.tools.ml.naivebayes
Package related to ML by means of the Naive Bayes algorithm.
opennlp.tools.ml.perceptron
Package related to ML by means of the perceptron algorithm.
opennlp.tools.namefind
Package related to finding proper names and numeric amounts.
opennlp.tools.parser
Package containing common code for performing full syntactic parsing.
opennlp.tools.parser.chunking
Package containing code for performing full syntactic parsing using shift/reduce-style decisions.
opennlp.tools.parser.treeinsert
Package containing experimental code for performing full syntactic parsing using attachment decisions.
opennlp.tools.postag
Package related to part-of-speech tagging.
opennlp.tools.sentdetect
Package related to identifying sentence boundaries.
opennlp.tools.tokenize
Contains classes related to finding token or words in a string.
opennlp.tools.util
Package containing utility data structures and algorithms used by multiple other packages.
opennlp.tools.util.model

- Classes in opennlp.tools.ml.model used by opennlp.tools.chunker
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
  Sequence
  Class which models a sequence.
  SequenceClassificationModel
  A classification model that can label an input `Sequence`.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.doccat
  Class
  Description
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.langdetect
  Class
  Description
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.lemmatizer
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
  Sequence
  Class which models a sequence.
  SequenceClassificationModel
  A classification model that can label an input `Sequence`.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml
  Class
  Description
  AbstractModelWriter
  An abstract, basic implementation of a model writer.
  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.
  DataIndexer
  Represents an indexer which compresses events in memory and performs feature selection.
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
  SequenceClassificationModel
  A classification model that can label an input `Sequence`.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml.maxent
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  Context
  Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
  DataIndexer
  Represents an indexer which compresses events in memory and performs feature selection.
  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.
  MaxentModel
  Interface for maximum entropy models.
  Prior
  This interface allows one to implement a prior distribution for use in maximum entropy model training.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml.maxent.io
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  AbstractModelReader
  An abstract, basic implementation of a model reader.
  AbstractModelWriter
  An abstract, basic implementation of a model writer.
  ComparablePredicate
  A maxent predicate representation which we can use to sort based on the outcomes.
  DataReader
  Describes generic ways to read data from a `DataInputStream`.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml.maxent.quasinewton
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  Context
  Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
  DataIndexer
  Represents an indexer which compresses events in memory and performs feature selection.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml.model
  Class
  Description
  AbstractDataIndexer
  Abstract `DataIndexer` implementation for collecting event and context counts used in training.
  AbstractModel
  A basic `MaxentModel` implementation.
  AbstractModel.ModelType
  AbstractModelReader
  An abstract, basic implementation of a model reader.
  AbstractModelWriter
  An abstract, basic implementation of a model writer.
  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.
  DataIndexer
  Represents an indexer which compresses events in memory and performs feature selection.
  DataReader
  Describes generic ways to read data from a `DataInputStream`.
  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`.
  MaxentModel
  Interface for maximum entropy models.
  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.
  Prior
  This interface allows one to implement a prior distribution for use in maximum entropy model training.
  Sequence
  Class which models a sequence.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml.naivebayes
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  AbstractModelReader
  An abstract, basic implementation of a model reader.
  AbstractModelWriter
  An abstract, basic implementation of a model writer.
  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.
  DataIndexer
  Represents an indexer which compresses events in memory and performs feature selection.
  DataReader
  Describes generic ways to read data from a `DataInputStream`.
  EvalParameters
  This class encapsulates the variables used in producing probabilities from a model and facilitates passing these variables to the eval method.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.ml.perceptron
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  AbstractModelReader
  An abstract, basic implementation of a model reader.
  AbstractModelWriter
  An abstract, basic implementation of a model writer.
  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.
  DataIndexer
  Represents an indexer which compresses events in memory and performs feature selection.
  DataReader
  Describes generic ways to read data from a `DataInputStream`.
  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.
  MaxentModel
  Interface for maximum entropy models.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.namefind
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
  Sequence
  Class which models a sequence.
  SequenceClassificationModel
  A classification model that can label an input `Sequence`.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.parser
  Class
  Description
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.parser.chunking
  Class
  Description
  Event
  The context of a decision point during training.
- Classes in opennlp.tools.ml.model used by opennlp.tools.parser.treeinsert
  Class
  Description
  Event
  The context of a decision point during training.
- Classes in opennlp.tools.ml.model used by opennlp.tools.postag
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
  Sequence
  Class which models a sequence.
  SequenceClassificationModel
  A classification model that can label an input `Sequence`.
  SequenceStream
  Interface for streams of `sequences` used to train sequence models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.sentdetect
  Class
  Description
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.tokenize
  Class
  Description
  Event
  The context of a decision point during training.
  MaxentModel
  Interface for maximum entropy models.
- Classes in opennlp.tools.ml.model used by opennlp.tools.util
  Class
  Description
  Event
  The context of a decision point during training.
- Classes in opennlp.tools.ml.model used by opennlp.tools.util.model
  Class
  Description
  AbstractModel
  A basic `MaxentModel` implementation.
  MaxentModel
  Interface for maximum entropy models.