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Packages that use de.jstacs.sequenceScores |
| de.jstacs.sequenceScores |
Provides all SequenceScores, which can be used to score a Sequence, typically using some model assumptions. |
| de.jstacs.sequenceScores.differentiable |
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| de.jstacs.sequenceScores.differentiable.logistic |
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| de.jstacs.sequenceScores.statisticalModels |
Provides all StatisticalModels, which can compute a proper (i.e., normalized) likelihood over the input space of sequences.
StatisticalModels can be further differentiated into TrainableStatisticalModels,
which can be learned from a single input DataSet, and DifferentiableStatisticalModels,
which define a proper likelihood but can also compute gradients like DifferentiableSequenceScores. |
| de.jstacs.sequenceScores.statisticalModels.differentiable |
Provides all DifferentiableStatisticalModels, which can compute the gradient with
respect to their parameters for a given input Sequence. |
| de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels |
Provides DifferentiableStatisticalModels that are directed graphical models. |
| de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous |
Provides DifferentiableStatisticalModels that are homogeneous, i.e. |
| de.jstacs.sequenceScores.statisticalModels.differentiable.mixture |
Provides DifferentiableSequenceScores that are mixtures of other DifferentiableSequenceScores. |
| de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif |
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| de.jstacs.sequenceScores.statisticalModels.trainable |
Provides all TrainableStatisticalModels, which can
be learned from a single DataSet. |
| de.jstacs.sequenceScores.statisticalModels.trainable.discrete |
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| de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous |
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| de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous |
This package contains various inhomogeneous models. |
| de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared |
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| de.jstacs.sequenceScores.statisticalModels.trainable.hmm |
The package provides all interfaces and classes for a hidden Markov model (HMM). |
| de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models |
The package provides different implementations of hidden Markov models based on AbstractHMM. |
| de.jstacs.sequenceScores.statisticalModels.trainable.mixture |
This package is the super package for any mixture model. |
| de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif |
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| de.jstacs.utils |
This package contains a bundle of useful classes and interfaces like ... |