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## Uses of Class
de.jstacs.sequenceScores.statisticalModels.differentiable.AbstractVariableLengthDiffSM

Packages that use AbstractVariableLengthDiffSM
de.jstacs.sequenceScores.statisticalModels.differentiable | Provides all `DifferentiableStatisticalModel`s, which can compute the gradient with respect to their parameters for a given input `Sequence`.
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous | Provides `DifferentiableStatisticalModel`s that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence

Uses of AbstractVariableLengthDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable

Subclasses of AbstractVariableLengthDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable
`class` | `CyclicMarkovModelDiffSM` This scoring function implements a cyclic Markov model of arbitrary order and periodicity for any sequence length.

Uses of AbstractVariableLengthDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Subclasses of AbstractVariableLengthDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
`class` | `HomogeneousDiffSM` This is the main class for all homogeneous `DifferentiableSequenceScore`s.
`class` | `HomogeneousMM0DiffSM` This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
`class` | `HomogeneousMMDiffSM` This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
`class` | `UniformHomogeneousDiffSM` This scoring function does nothing.

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