Uses of Package de.jstacs.algorithms.optimization

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Packages that use de.jstacs.algorithms.optimization
Package	Description
de.jstacs.algorithms.optimization	Provides classes for different types of algorithms that are not directly linked to the modelling components of Jstacs: Algorithms on graphs, algorithms for numerical optimization, and a basic alignment algorithm.
de.jstacs.classifiers.differentiableSequenceScoreBased	Provides the classes for `Classifier`s that are based on `SequenceScore`s. It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior.
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix	Provides an implementation of a classifier that allows to train the parameters of a set of `DifferentiableStatisticalModel`s by a unified generative-discriminative learning principle.
de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior	Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors.
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling	Provides the classes for `AbstractScoreBasedClassifier`s that are based on `SamplingDifferentiableStatisticalModel`s and that sample parameters using the Metropolis-Hastings algorithm.
de.jstacs.motifDiscovery	This package provides the framework including the interface for any de novo motif discoverer.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous	This package contains various inhomogeneous models.

Classes in de.jstacs.algorithms.optimization used by de.jstacs.algorithms.optimization
Class and Description
DifferentiableFunction This class is the framework for any (at least) one time differentiable function $f: \mathbb{R}^n \to \mathbb{R}$ .
DimensionException This class is for `Exception`s depending on wrong dimensions of vectors for a given function.
EvaluationException This class indicates that there was a problem to evaluate a function or the gradient of the function.
Function This interface is the framework for any mathematical function $f: \mathbb{R}^n \to \mathbb{R}$ .
OneDimensionalFunction This class implements the interface `Function` for an one-dimensional function.
StartDistanceForecaster This interface is used to determine the next start distance that will be used in a line search.
TerminationException This class is for an `Exception` that is thrown if something with a termination was not correct.

Classes in de.jstacs.algorithms.optimization used by de.jstacs.classifiers.differentiableSequenceScoreBased
Class and Description
DifferentiableFunction This class is the framework for any (at least) one time differentiable function $f: \mathbb{R}^n \to \mathbb{R}$ .
DimensionException This class is for `Exception`s depending on wrong dimensions of vectors for a given function.
EvaluationException This class indicates that there was a problem to evaluate a function or the gradient of the function.
Function This interface is the framework for any mathematical function $f: \mathbb{R}^n \to \mathbb{R}$ .
MultiThreadedFunction This interface defines methods for functions that are multi-threaded.

Classes in de.jstacs.algorithms.optimization used by de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
Class and Description
DifferentiableFunction This class is the framework for any (at least) one time differentiable function $f: \mathbb{R}^n \to \mathbb{R}$ .
DimensionException This class is for `Exception`s depending on wrong dimensions of vectors for a given function.
EvaluationException This class indicates that there was a problem to evaluate a function or the gradient of the function.
Function This interface is the framework for any mathematical function $f: \mathbb{R}^n \to \mathbb{R}$ .
MultiThreadedFunction This interface defines methods for functions that are multi-threaded.

Classes in de.jstacs.algorithms.optimization used by de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior
Class and Description
DifferentiableFunction This class is the framework for any (at least) one time differentiable function $f: \mathbb{R}^n \to \mathbb{R}$ .
DimensionException This class is for `Exception`s depending on wrong dimensions of vectors for a given function.
EvaluationException This class indicates that there was a problem to evaluate a function or the gradient of the function.
Function This interface is the framework for any mathematical function $f: \mathbb{R}^n \to \mathbb{R}$ .

Classes in de.jstacs.algorithms.optimization used by de.jstacs.classifiers.differentiableSequenceScoreBased.sampling
Class and Description
Function This interface is the framework for any mathematical function $f: \mathbb{R}^n \to \mathbb{R}$ .

Classes in de.jstacs.algorithms.optimization used by de.jstacs.motifDiscovery
Class and Description
DifferentiableFunction This class is the framework for any (at least) one time differentiable function $f: \mathbb{R}^n \to \mathbb{R}$ .
StartDistanceForecaster This interface is used to determine the next start distance that will be used in a line search.

Classes in de.jstacs.algorithms.optimization used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous
Class and Description
DifferentiableFunction This class is the framework for any (at least) one time differentiable function $f: \mathbb{R}^n \to \mathbb{R}$ .
DimensionException This class is for `Exception`s depending on wrong dimensions of vectors for a given function.
Function This interface is the framework for any mathematical function $f: \mathbb{R}^n \to \mathbb{R}$ .

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