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## Uses of Class
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM

Packages that use BayesianNetworkDiffSM
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.directedGraphicalModels | Provides `DifferentiableStatisticalModel`s that are directed graphical models.

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

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable that return BayesianNetworkDiffSM
`static BayesianNetworkDiffSM` | `DifferentiableStatisticalModelFactory.createInhomogeneousMarkovModel(AlphabetContainer con, int length, double ess, int order)` This method returns a inhomogeneous Markov model (IMM) with user-specified order.
`static BayesianNetworkDiffSM` | `DifferentiableStatisticalModelFactory.createPWM(AlphabetContainer con, int length, double ess)` This method returns a position weight matrix (PWM).

Uses of BayesianNetworkDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Subclasses of BayesianNetworkDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
`class` | `MarkovModelDiffSM` This class implements a `AbstractDifferentiableStatisticalModel` for an inhomogeneous Markov model.

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels that return BayesianNetworkDiffSM
`BayesianNetworkDiffSM` | `BayesianNetworkDiffSM.clone()`

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