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## Package de.jstacs.models

Provides the interface `Model` and its abstract implementation `AbstractModel`, which is the super class of all other models.

See:
Description

Interface Summary
Model | This interface defines all methods for a probabilistic model.

Class Summary
AbstractModel | Abstract class for a model for pattern recognition.
CompositeModel | This class is for modelling sequences by modelling the different positions of the each sequence by different models.
ModelFactory | This class allows to easily create some frequently used models.
NormalizableScoringFunctionModel | This model can be used to use a NormalizableScoringFunction as model.
UniformModel | This class represents a uniform model.
VariableLengthWrapperModel | This class allows to train any `Model` on `Sample`s of `Sequence`s with variable length if each individual length is at least `Model.getLength()`.

## Package de.jstacs.models Description

Provides the interface `Model` and its abstract implementation `AbstractModel`, which is the super class of all other models. The `Model` interface defines how to obtain a probability for a sequence and how to train the parameters of the model using a `Sample`. Any combination of `Models` can be used to build a `ModelBasedClassifier`, which can be evaluated in a `ClassifierAssessment`.

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