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## Uses of Interface
de.jstacs.InstantiableFromParameterSet

Packages that use InstantiableFromParameterSet
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.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.models.discrete |
de.jstacs.models.discrete.homogeneous |
de.jstacs.models.discrete.inhomogeneous | This package contains various inhomogeneous models.
de.jstacs.models.mixture.gibbssampling | This package contains many classes that can be used while a Gibbs sampling.
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.scoringFunctions.directedGraphicalModels | Provides `ScoringFunction`s that are equivalent to directed graphical models.
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures | Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction`.
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures | Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction` as a Bayesian tree using a number of measures to define a rating of structures
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures | Provides the facilities to learn the structure of a `BayesianNetworkScoringFunction` as a permuted Markov model using a number of measures to define a rating of structures
de.jstacs.utils | This package contains a bundle of useful classes and interfaces like ...

Uses of InstantiableFromParameterSet in de.jstacs.data

Classes in de.jstacs.data that implement InstantiableFromParameterSet
`class` | `Alphabet` Class for a set of symbols, i.e. an `Alphabet`.
`class` | `AlphabetContainer` The container for `Alphabet`s used in a `Sequence`, `Sample`, `AbstractModel` or ... .

Uses of InstantiableFromParameterSet in de.jstacs.data.alphabets

Classes in de.jstacs.data.alphabets that implement InstantiableFromParameterSet
`class` | `ComplementableDiscreteAlphabet` This abstract class indicates that an alphabet can be used to compute the complement.
`class` | `ContinuousAlphabet` Class for a continuous alphabet.
`class` | `DiscreteAlphabet` Class for an alphabet that consists of arbitrary `String`s.
`class` | `DNAAlphabet` This class implements the discrete alphabet that is used for DNA.

Uses of InstantiableFromParameterSet in de.jstacs.io

Methods in de.jstacs.io that return InstantiableFromParameterSet
`static InstantiableFromParameterSet` | `ParameterSetParser.getInstanceFromParameterSet(InstanceParameterSet pars)` Returns an instance of a subclass of `InstantiableFromParameterSet` that can be instantiated by the `InstanceParameterSet` `pars`.
`static InstantiableFromParameterSet` | `ParameterSetParser.getInstanceFromParameterSet(ParameterSet pars, Class instanceClass)` Returns an instance of a subclass of `InstantiableFromParameterSet` that can be instantiated by the `ParameterSet` `pars`.

Uses of InstantiableFromParameterSet in de.jstacs.models.discrete

Classes in de.jstacs.models.discrete that implement InstantiableFromParameterSet
`class` | `DiscreteGraphicalModel` This is the main class for all discrete graphical models (DGM).

Uses of InstantiableFromParameterSet in de.jstacs.models.discrete.homogeneous

Classes in de.jstacs.models.discrete.homogeneous that implement InstantiableFromParameterSet
`class` | `HomogeneousMM` This class implements homogeneous Markov models (hMM) of arbitrary order.
`class` | `HomogeneousModel` This class implements homogeneous models of arbitrary order.

Uses of InstantiableFromParameterSet in de.jstacs.models.discrete.inhomogeneous

Classes in de.jstacs.models.discrete.inhomogeneous that implement InstantiableFromParameterSet
`class` | `BayesianNetworkModel` The class implements a Bayesian network ( `StructureLearner.ModelType.BN` ) of fixed order.
`class` | `DAGModel` The abstract class for directed acyclic graphical models (`DAGModel`).
`class` | `FSDAGModel` This class can be used for any discrete fixed structure directed acyclic graphical model ( `FSDAGModel`).
`class` | `InhomogeneousDGM` This class is the main class for all inhomogeneous discrete graphical models (`InhomogeneousDGM`).

Uses of InstantiableFromParameterSet in de.jstacs.models.mixture.gibbssampling

Classes in de.jstacs.models.mixture.gibbssampling that implement InstantiableFromParameterSet
`class` | `FSDAGModelForGibbsSampling` This is the class for a fixed structure directed acyclic graphical model (see `FSDAGModel`) that can be used in a Gibbs sampling.

Uses of InstantiableFromParameterSet in de.jstacs.parameters

Methods in de.jstacs.parameters that return InstantiableFromParameterSet
`InstantiableFromParameterSet` | `InstanceParameterSet.getInstance()` Returns a new instance of the class of `InstanceParameterSet.getInstanceClass()` that was created using this `ParameterSet`.

Uses of InstantiableFromParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels

Classes in de.jstacs.scoringFunctions.directedGraphicalModels that implement InstantiableFromParameterSet
`class` | `BayesianNetworkScoringFunction` This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
`class` | `MutableMarkovModelScoringFunction` This class implements a `AbstractNormalizableScoringFunction` for an inhomogeneous Markov model.

Uses of InstantiableFromParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures

Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures that implement InstantiableFromParameterSet
`class` | `InhomogeneousMarkov` Class for a network structure of a `BayesianNetworkScoringFunction` that is an inhomogeneous Markov model.
`class` | `Measure` Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data.

Uses of InstantiableFromParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures

Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures that implement InstantiableFromParameterSet
`class` | `BTExplainingAwayResidual` Structure learning `Measure` that computes a maximum spanning tree based on the explaining away residual and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a `BayesianNetworkScoringFunction` .
`class` | `BTMutualInformation` Structure learning `Measure` that computes a maximum spanning tree based on mutual information and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a `BayesianNetworkScoringFunction` .

Uses of InstantiableFromParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures

Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures that implement InstantiableFromParameterSet
`class` | `PMMExplainingAwayResidual` Class for the network structure of a `BayesianNetworkScoringFunction` that is a permuted Markov model based on the explaining away residual.
`class` | `PMMMutualInformation` Class for the network structure of a `BayesianNetworkScoringFunction` that is a permuted Markov model based on mutual information.

Uses of InstantiableFromParameterSet in de.jstacs.utils

Method parameters in de.jstacs.utils with type arguments of type InstantiableFromParameterSet
`static LinkedList<Class<? extends InstanceParameterSet>>` | `SubclassFinder.getParameterSetFor(Class<? extends InstantiableFromParameterSet> clazz)` Returns a `LinkedList` of the classes of the `InstanceParameterSet`s that can be used to instantiate the sub-class of `InstantiableFromParameterSet` that is given by `clazz`

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