StatisticalModel
s, which can compute a proper (i.e., normalized) likelihood over the input space of sequences.StatisticalModel
s can be further differentiated into TrainableStatisticalModel
s,
which can be learned from a single input DataSet
, and DifferentiableStatisticalModel
s,
which define a proper likelihood but can also compute gradients like DifferentiableSequenceScore
s.See: Description
Interface | Description |
---|---|
StatisticalModel |
This interface declares methods of a statistical model, i.e., a
SequenceScore that defines a proper likelihood
over the input Sequence s. |
StatisticalModel
s, which can compute a proper (i.e., normalized) likelihood over the input space of sequences.StatisticalModel
s can be further differentiated into TrainableStatisticalModel
s,
which can be learned from a single input DataSet
, and DifferentiableStatisticalModel
s,
which define a proper likelihood but can also compute gradients like DifferentiableSequenceScore
s.
These can be found in the sub-packages de.jstacs.sequenceScores.statisticalModels.trainable
and de.jstacs.sequenceScores.statisticalModels.differentiable
, respectively.