Object which compresses events in memory and performs feature selection.
Interface for maximum entropy models.
This interface allows one to implement a prior distribution for use in maximum entropy model training.
A classification model that can label an input sequence.
Interface for streams of sequences used to train sequence models.
Abstract class for collecting event and context counts used in training.
A maxent event representation which we can use to sort based on the predicates indexes contained in the events.
A maxent predicate representation which we can use to sort based on the outcomes.
Class which associates a real valued parameter or expected value with a particular contextual predicate or feature.
This class encapsulates the varibales used in producing probabilities from a model and facilitaes passing these variables to the eval method.
The context of a decision point during training.
Class for using a file of events as an event stream.
Class used to store parameters or expected values associated with this context which can be updated or assigned.
An indexer for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates.
An indexer 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.
Class which models a sequence.
Class which turns a sequence stream into an event stream.
Collecting event and context counts by making two passes over the events.
Provide a maximum entropy model with a uniform prior.
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