Packages |
de.jstacs |
This package is the root package for the most and important packages. |
de.jstacs.algorithms.alignment |
Provides classes for alignments |
de.jstacs.algorithms.alignment.cost |
Provides classes for cost functions used in alignments |
de.jstacs.algorithms.graphs |
Provides classes for algorithms on graphs. |
de.jstacs.algorithms.graphs.tensor |
Provides classes to represent symmetric and asymmetric tensors in graphs |
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.
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de.jstacs.algorithms.optimization.termination |
Provides classes for termination conditions that can be used in algorithms |
de.jstacs.classifiers |
This package provides the framework for any classifier. |
de.jstacs.classifiers.assessment |
This package allows to assess classifiers. |
de.jstacs.classifiers.differentiableSequenceScoreBased |
Provides the classes for Classifier s that are based on SequenceScore s. |
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.msp |
Provides an implementation of a classifier that allows to train the parameters of a set of
DifferentiableStatisticalModel s either
by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL) |
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.classifiers.performanceMeasures |
This package provides the implementations of performance measures that can be used to assess any classifier |
de.jstacs.classifiers.trainSMBased |
Provides the classes for Classifier s that are based on TrainableStatisticalModel s |
de.jstacs.classifiers.utils |
Provides some useful classes for working with classifiers |
de.jstacs.data |
Provides classes for the representation of data. |
de.jstacs.data.alphabets |
Provides classes for the representation of discrete and continuous alphabets, including a DNAAlphabet for the most common case of DNA-sequences |
de.jstacs.data.bioJava |
Provides an adapter between the representation of data in BioJava and the representation used in Jstacs. |
de.jstacs.data.sequences |
Provides classes for representing sequences. |
de.jstacs.data.sequences.annotation |
Provides the facilities to annotate Sequence s using a number of pre-defined annotation types, or additional
implementations of the SequenceAnnotation class |
de.jstacs.io |
Provides classes for reading data from and writing to a file and storing a number of datatypes, including all primitives, arrays of primitives, and Storable s to an XML-representation |
de.jstacs.motifDiscovery |
This package provides the framework including the interface for any de novo motif discoverer |
de.jstacs.motifDiscovery.history |
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de.jstacs.parameters |
This package provides classes for parameters that establish a general convention for the description of parameters
as defined in the Parameter -interface. |
de.jstacs.parameters.validation |
Provides classes for the validation of Parameter values |
de.jstacs.results |
This package provides classes for results and sets of results. |
de.jstacs.sampling |
This package contains many classes that can be used while a sampling. |
de.jstacs.sequenceScores |
Provides all SequenceScore s, 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 StatisticalModel s, which can compute a proper (i.e., normalized) likelihood over the input space of sequences. |
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. |
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures |
Provides the facilities to learn the structure of a BayesianNetworkDiffSM . |
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures |
Provides the facilities to learn the structure of a BayesianNetworkDiffSM as
a Bayesian tree using a number of measures to define a rating of structures |
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures |
Provides the facilities to learn the structure of a BayesianNetworkDiffSM as
a permuted Markov model using a number of measures to define a rating of structures |
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous |
Provides DifferentiableStatisticalModel s that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence |
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture |
Provides DifferentiableSequenceScore s that are mixtures of other DifferentiableSequenceScore s. |
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif |
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de.jstacs.sequenceScores.statisticalModels.trainable |
Provides all TrainableStatisticalModel s, 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.homogeneous.parameters |
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de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous |
This package contains various inhomogeneous models. |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters |
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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.hmm.states |
The package provides all interfaces and classes for states used in hidden Markov models. |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions |
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de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous |
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de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete |
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de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training |
The package provides all classes used to determine the training algorithm of a hidden Markov model |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions |
The package provides all interfaces and classes for transitions used in hidden Markov models. |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements |
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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.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior |
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de.jstacs.sequenceScores.statisticalModels.trainable.phylo |
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de.jstacs.sequenceScores.statisticalModels.trainable.phylo.parser |
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de.jstacs.utils |
This package contains a bundle of useful classes and interfaces like ... |
de.jstacs.utils.galaxy |
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de.jstacs.utils.random |
This package contains some classes for generating random numbers |