Models have features, and this defines the mapping from indices in the weight vector to features.
Caches the weights using the cache broker.
just saves feature weights to disk as a serialized counter.
just saves feature weights to disk as a serialized counter. The file is prefix.ser.gz
(Since version ) see corresponding Javadoc for more information.
A Model represents a class for turning weight vectors into epic.framework.Inferences. It's main job is to hook up with a epic.framework.ModelObjective and mediate computation of ExpectedCounts and conversion to the objective that's needed for optimization.
the kind of