Provides all {@link de.jstacs.sequenceScores.SequenceScore}s, which can be used to score a {@link de.jstacs.data.sequences.Sequence}, typically using some model assumptions. Important special cases of {@link de.jstacs.sequenceScores.SequenceScore}s are {@link de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore}s, which can compute the gradient with respect to their parameter for a given input sequence, including logistic regression, and {@link de.jstacs.sequenceScores.statisticalModels.StatisticalModel}s, which can compute a proper (i.e., normalized) likelihood over the input space of sequences. These are located in the sub-package {@link de.jstacs.sequenceScores.statisticalModels}.
{@link de.jstacs.sequenceScores.statisticalModels.StatisticalModel}s can be further differentiated into {@link de.jstacs.sequenceScores.statisticalModels.trainable.TrainableStatisticalModel}s, which can be learned from a single input {@link de.jstacs.data.DataSet}, and {@link de.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel}s, which define a proper likelihood but can also compute gradients like {@link de.jstacs.sequenceScores.differentiable.DifferentiableSequenceScore}s.