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## Uses of Class
de.jstacs.parameters.InstanceParameterSet

Packages that use InstanceParameterSet
de.jstacs | This package is the root package for the most and important packages.
de.jstacs.classifier.scoringFunctionBased | Provides the classes for `Classifier`s that are based on `ScoringFunction`s.
de.jstacs.classifier.scoringFunctionBased.cll | Provides the implementation of the log conditional likelihood as an `OptimizableFunction` and a classifier that uses log conditional likelihood or supervised posterior to learn the parameters of a set of `ScoringFunctions`
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.parameters |
de.jstacs.models.discrete.inhomogeneous.parameters |
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 InstanceParameterSet in de.jstacs

Methods in de.jstacs that return InstanceParameterSet
`InstanceParameterSet` | `InstantiableFromParameterSet.getCurrentParameterSet()` Returns the `InstanceParameterSet` that has been used to instantiate the current instance of the implementing class.

Uses of InstanceParameterSet in de.jstacs.classifier.scoringFunctionBased

Subclasses of InstanceParameterSet in de.jstacs.classifier.scoringFunctionBased
`class` | `ScoreClassifierParameterSet` A set of `Parameter`s for any `ScoreClassifier`.

Uses of InstanceParameterSet in de.jstacs.classifier.scoringFunctionBased.cll

Subclasses of InstanceParameterSet in de.jstacs.classifier.scoringFunctionBased.cll
`class` | `CLLClassifierParameterSet` This class contains the parameters for the `CLLClassifier`.

Uses of InstanceParameterSet in de.jstacs.data

Subclasses of InstanceParameterSet in de.jstacs.data
`static class` | `Alphabet.AlphabetParameterSet` The super class for the `InstanceParameterSet` of any `Alphabet`.
`class` | `AlphabetContainerParameterSet` Class for the `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` of an `AlphabetContainer`.

Uses of InstanceParameterSet in de.jstacs.data.alphabets

Subclasses of InstanceParameterSet in de.jstacs.data.alphabets
`static class` | `ContinuousAlphabet.ContinuousAlphabetParameterSet` Class for the `ParameterSet` of a `ContinuousAlphabet`.
`static class` | `DiscreteAlphabet.DiscreteAlphabetParameterSet` Class for the `ParameterSet` of a `DiscreteAlphabet`.
`static class` | `DNAAlphabet.DNAAlphabetParameterSet` The parameter set for a `DNAAlphabet`.

Uses of InstanceParameterSet in de.jstacs.io

Methods in de.jstacs.io with parameters of type InstanceParameterSet
`static InstantiableFromParameterSet` | `ParameterSetParser.getInstanceFromParameterSet(InstanceParameterSet pars)` Returns an instance of a subclass of `InstantiableFromParameterSet` that can be instantiated by the `InstanceParameterSet` `pars`.

Uses of InstanceParameterSet in de.jstacs.models.discrete

Subclasses of InstanceParameterSet in de.jstacs.models.discrete
`class` | `DGMParameterSet` The super `ParameterSet` for any parameter set of a `DiscreteGraphicalModel`.

Uses of InstanceParameterSet in de.jstacs.models.discrete.homogeneous.parameters

Subclasses of InstanceParameterSet in de.jstacs.models.discrete.homogeneous.parameters
`class` | `HomMMParameterSet` This class implements a container for all parameters of a homogeneous Markov model.
`class` | `HomogeneousModelParameterSet` This class implements a container for all parameters of any homogeneous model.

Uses of InstanceParameterSet in de.jstacs.models.discrete.inhomogeneous.parameters

Subclasses of InstanceParameterSet in de.jstacs.models.discrete.inhomogeneous.parameters
`class` | `BayesianNetworkModelParameterSet` The `ParameterSet` for the class `BayesianNetworkModel`.
`class` | `FSDAGMParameterSet` The class for the parameters of a `FSDAGModel` (fixed structure directed acyclic graphical model).
`class` | `IDGMParameterSet` This is the abstract container of parameters that is a root container for all inhomogeneous discrete graphical model parameter containers.

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

Subclasses of InstanceParameterSet in de.jstacs.models.mixture.gibbssampling
`class` | `FSDAGModelForGibbsSamplingParameterSet` The class for the parameters of a `FSDAGModelForGibbsSampling`.

Uses of InstanceParameterSet in de.jstacs.parameters

Subclasses of InstanceParameterSet in de.jstacs.parameters
`class` | `SequenceScoringParameterSet` Abstract class for a `ParameterSet` containing all parameters necessary to construct an `Object` that implements `InstantiableFromParameterSet`.

Constructors in de.jstacs.parameters with parameters of type InstanceParameterSet
`CollectionParameter(InstanceParameterSet[] values, String name, String comment, boolean required)` Constructor for a `CollectionParameter` from an array of `ParameterSet`s.
`MultiSelectionCollectionParameter(InstanceParameterSet[] values, String name, String comment, boolean required)` Creates a new `MultiSelectionCollectionParameter` from an array of `ParameterSet`s.

Uses of InstanceParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels

Subclasses of InstanceParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels
`class` | `BayesianNetworkScoringFunctionParameterSet` Class for the parameters of a `BayesianNetworkScoringFunction`.

Methods in de.jstacs.scoringFunctions.directedGraphicalModels that return InstanceParameterSet
`InstanceParameterSet` | `BayesianNetworkScoringFunction.getCurrentParameterSet()`

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

Subclasses of InstanceParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures
`static class` | `InhomogeneousMarkov.InhomogeneousMarkovParameterSet` Class for an `InstanceParameterSet` that defines the parameters of an `InhomogeneousMarkov` structure `Measure`.

Methods in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures that return InstanceParameterSet
`InstanceParameterSet` | `InhomogeneousMarkov.getCurrentParameterSet()`

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

Subclasses of InstanceParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
`static class` | `BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet` Class for the parameters of a `BTExplainingAwayResidual` structure `Measure`.
`static class` | `BTMutualInformation.BTMutualInformationParameterSet` Class for the parameters of a `BTMutualInformation` structure `Measure`.

Methods in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures that return InstanceParameterSet
`InstanceParameterSet` | `BTMutualInformation.getCurrentParameterSet()`
`InstanceParameterSet` | `BTExplainingAwayResidual.getCurrentParameterSet()`

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

Subclasses of InstanceParameterSet in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
`static class` | `PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet` Class for the parameters of a `PMMExplainingAwayResidual` structure `Measure`.
`static class` | `PMMMutualInformation.PMMMutualInformationParameterSet` Class for the parameters of a `PMMMutualInformation` structure `Measure`.

Methods in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures that return InstanceParameterSet
`InstanceParameterSet` | `PMMMutualInformation.getCurrentParameterSet()`
`InstanceParameterSet` | `PMMExplainingAwayResidual.getCurrentParameterSet()`

Uses of InstanceParameterSet in de.jstacs.utils

Methods in de.jstacs.utils that return types with arguments of type InstanceParameterSet
`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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