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

Packages that use ParameterSet
de.jstacs.algorithms.optimization.termination | Provides classes for termination conditions that can be used in algorithms
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.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.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.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.sampling | This package contains many classes that can be used while a sampling.
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.trainable.discrete |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters |
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.utils | This package contains a bundle of useful classes and interfaces like ...
de.jstacs.utils.galaxy |

Uses of ParameterSet in de.jstacs.algorithms.optimization.termination

Subclasses of ParameterSet in de.jstacs.algorithms.optimization.termination
`static class` | `AbsoluteValueCondition.AbsoluteValueConditionParameterSet` Deprecated. This class implements the parameter set for a `AbsoluteValueCondition`.
`static class` | `AbstractTerminationCondition.AbstractTerminationConditionParameterSet` This class implements the super class of all parameter sets of instances from `AbstractTerminationCondition`.
`static class` | `CombinedCondition.CombinedConditionParameterSet` This class implements the parameter set for a `CombinedCondition`.
`static class` | `IterationCondition.IterationConditionParameterSet` This class implements the parameter set for a `IterationCondition`.
`static class` | `SmallDifferenceOfFunctionEvaluationsCondition.SmallDifferenceOfFunctionEvaluationsConditionParameterSet` This class implements the parameter set for a `SmallDifferenceOfFunctionEvaluationsCondition`.
`static class` | `SmallGradientConditon.SmallGradientConditonParameterSet` This class implements the parameter set for a `SmallStepCondition`.
`static class` | `SmallStepCondition.SmallStepConditionParameterSet` This class implements the parameter set for a `SmallStepCondition`.
`static class` | `TimeCondition.TimeConditionParameterSet` This class implements the parameter set for a `TimeCondition`.

Uses of ParameterSet in de.jstacs.classifiers.assessment

Subclasses of ParameterSet in de.jstacs.classifiers.assessment
`class` | `ClassifierAssessmentAssessParameterSet` This class is the superclass used by all `ClassifierAssessmentAssessParameterSet`s.
`class` | `KFoldCrossValidationAssessParameterSet` This class implements a `ClassifierAssessmentAssessParameterSet` that must be used to call method `assess( ... )` of a `KFoldCrossValidation`.
`class` | `RepeatedHoldOutAssessParameterSet` This class implements a `ClassifierAssessmentAssessParameterSet` that must be used to call method `assess( ... )` of a `RepeatedHoldOutExperiment`.
`class` | `RepeatedSubSamplingAssessParameterSet` This class implements a `ClassifierAssessmentAssessParameterSet` that must be used to call method `assess( ... )` of a `RepeatedSubSamplingExperiment`.
`class` | `Sampled_RepeatedHoldOutAssessParameterSet` This class implements a `ClassifierAssessmentAssessParameterSet` that must be used to call the method `assess( ... )` of a `Sampled_RepeatedHoldOutExperiment`.

Uses of ParameterSet in de.jstacs.classifiers.differentiableSequenceScoreBased

Subclasses of ParameterSet in de.jstacs.classifiers.differentiableSequenceScoreBased
`class` | `ScoreClassifierParameterSet` A set of `Parameter`s for any `ScoreClassifier`.

Uses of ParameterSet in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix

Subclasses of ParameterSet in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
`class` | `GenDisMixClassifierParameterSet` This class contains the parameters for the `GenDisMixClassifier`.

Uses of ParameterSet in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling

Subclasses of ParameterSet in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling
`class` | `SamplingGenDisMixClassifierParameterSet` `ParameterSet` to instantiate a `SamplingGenDisMixClassifier`.
`class` | `SamplingScoreBasedClassifierParameterSet` `ParameterSet` to instantiate a `SamplingScoreBasedClassifier`.

Uses of ParameterSet in de.jstacs.classifiers.performanceMeasures

Subclasses of ParameterSet in de.jstacs.classifiers.performanceMeasures
`class` | `AbstractPerformanceMeasure` This class is the abstract super class of any performance measure used to evaluate an `AbstractClassifier`.
`class` | `AucPR` This class implements the area under curve of the precision-recall curve.
`class` | `AucROC` This class implements the area under curve of the Receiver Operating Characteristics curve.
`class` | `ClassificationRate` This class implements the classification rate, i.e.
`class` | `ConfusionMatrix` This class implements the performance measure confusion matrix.
`class` | `FalsePositiveRateForFixedSensitivity` This class implements the false positive rate for a fixed sensitivity.
`class` | `MaximumCorrelationCoefficient` This class implements the maximum of the correlation coefficient .
`class` | `MaximumFMeasure` Computes the maximum of the general F-measure given a positive real parameter .
`class` | `MaximumNumericalTwoClassMeasure` This class prepares everything for an easy implementation of a maximum of any numerical performance measure.
`class` | `NumericalPerformanceMeasureParameterSet` This class implements a container for `NumericalPerformanceMeasure`s that can be used, for instance, in an repeated assessment, (cf.
`class` | `PerformanceMeasureParameterSet` This class implements a container of `AbstractPerformanceMeasure`s that can be used in `AbstractClassifier.evaluate(PerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...)`.
`class` | `PositivePredictiveValueForFixedSensitivity` This class implements the positive predictive value for a fixed sensitivity.
`class` | `PRCurve` This class implements the precision-recall curve and its area under the curve.
`class` | `ROCCurve` This class implements the Receiver Operating Characteristics curve and the area under the curve.
`class` | `SensitivityForFixedSpecificity` This class implements the sensitivity for a fixed specificity.
`class` | `TwoClassAbstractPerformanceMeasure` This class is the abstract super class of any performance measure that can only be computed for binary classifiers.

Uses of ParameterSet in de.jstacs.data

Subclasses of ParameterSet in de.jstacs.data
`static class` | `AlphabetContainer.AbstractAlphabetContainerParameterSet<T extends AlphabetContainer>` This class is the super class of any `InstanceParameterSet` for `AlphabetContainer`.
`class` | `AlphabetContainerParameterSet` Class for the `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` of an `AlphabetContainer`.
`static class` | `AlphabetContainerParameterSet.AlphabetArrayParameterSet` Class for the parameters of an array of `Alphabet`s of defined length.
`static class` | `AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet` Class for the parameter set of an array of `Alphabet`s where each `Alphabet` may be used for one or more sections of positions.

Uses of ParameterSet in de.jstacs.data.alphabets

Subclasses of ParameterSet in de.jstacs.data.alphabets
`static class` | `Alphabet.AlphabetParameterSet<T extends Alphabet>` The super class for the `InstanceParameterSet` of any `Alphabet`.
`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`.
`static class` | `DNAAlphabetContainer.DNAAlphabetContainerParameterSet` This class implements a singleton for the `ParameterSet` of a `DNAAlphabetContainer`.
`static class` | `GenericComplementableDiscreteAlphabet.GenericComplementableDiscreteAlphabetParameterSet` This class is used as container for the parameters of a `GenericComplementableDiscreteAlphabet`.
`static class` | `ProteinAlphabet.ProteinAlphabetParameterSet` The parameter set for a `ProteinAlphabet`.

Uses of ParameterSet in de.jstacs.io

Methods in de.jstacs.io with parameters of type ParameterSet
`static
`<T extends InstantiableFromParameterSet> T`
` | `ParameterSetParser.getInstanceFromParameterSet(ParameterSet pars, Class<T> instanceClass)` Returns an instance of a subclass of `InstantiableFromParameterSet` that can be instantiated by the `ParameterSet` `pars`.

Uses of ParameterSet in de.jstacs.parameters

Subclasses of ParameterSet in de.jstacs.parameters
`class` | `ArrayParameterSet` Class for a `ParameterSet` that consists of a length-`Parameter` that defines the length of the array and an array of `ParameterSetContainer`s of this length.
`class` | `ExpandableParameterSet` A class for a `ParameterSet` that can be expanded by additional `Parameter`s at runtime.
`class` | `InstanceParameterSet<T extends InstantiableFromParameterSet>` Container class for a set of `Parameter`s that can be used to instantiate another class.
`class` | `SequenceScoringParameterSet<T extends InstantiableFromParameterSet>` Abstract class for a `ParameterSet` containing all parameters necessary to construct an `Object` that implements `InstantiableFromParameterSet`.
`class` | `SimpleParameterSet` Class for a `ParameterSet` that is constructed from an array of `Parameter`s.

Fields in de.jstacs.parameters declared as ParameterSet
`protected ParameterSet` | `AbstractSelectionParameter.parameters` The internal `ParameterSet` that holds the possible values
`protected ParameterSet` | `Parameter.parent` If this `Parameter` is enclosed in a `ParameterSet`, this variable holds a reference to that `ParameterSet`.
`protected ParameterSet` | `ExpandableParameterSet.template` The template for each `ParameterSet`

Methods in de.jstacs.parameters that return ParameterSet
`ParameterSet` | `ParameterSet.clone()` Creates a full clone (deep copy) of this `ParameterSet`.
`ParameterSet` | `AbstractSelectionParameter.getParametersInCollection()` Returns the possible values in this collection.
`ParameterSet` | `Parameter.getParent()` Returns a reference to the `ParameterSet` enclosing this `Parameter`.
`ParameterSet` | `ParameterSetContainer.getValue()`

Methods in de.jstacs.parameters with parameters of type ParameterSet
`static String` | `ParameterSet.getComment(ParameterSet p)` Returns a comment for the `ParameterSet`.
`static String` | `ParameterSet.getName(ParameterSet p)` Returns a name for the `ParameterSet`.
`boolean` | `ParameterSet.isComparable(ParameterSet p)` This method checks whether the given `ParameterSet` is comparable to the current instance, i.e. whether the `Class` and the number of parameters are identical, and the individual `Parameter`s are comparable.
`boolean` | `ExpandableParameterSet.replaceContentWith(ParameterSet[] paramSetArray)` First removes all previous added `ParameterSetContainer`s and afterwards adds all given `ParameterSet`s (in the given order) enclosed in new `ParameterSetContainer`s.
`void` | `Parameter.setParent(ParameterSet parent)` Sets the reference of the enclosing `ParameterSet` of this `Parameter` to `parent`.

Method parameters in de.jstacs.parameters with type arguments of type ParameterSet
`static String` | `ParameterSet.getComment(Class<? extends ParameterSet> c)` Returns a comment for the class.
`static String` | `ParameterSet.getName(Class<? extends ParameterSet> c)` Returns a name for the class.

Constructors in de.jstacs.parameters with parameters of type ParameterSet
`AbstractSelectionParameter(String name, String comment, boolean required, ParameterSet... values)` Constructor for a `AbstractSelectionParameter` from an array of `ParameterSet`s.
`ArrayParameterSet(ParameterSet template, String nameTemplate, String commentTemplate)` Creates a new `ArrayParameterSet` from a `Class` that can be instantiated using this `ArrayParameterSet` and templates for the `ParameterSet` in each element of the array, the name and the comment that are displayed for the `ParameterSetContainer`s enclosing the `ParameterSet`s.
`ArrayParameterSet(ParameterSet template, String nameTemplate, String commentTemplate, String lengthName, String lengthComment, NumberValidator<Integer> allowedLengths)` Creates a new `ArrayParameterSet` from a `Class` that can be instantiated using this `ArrayParameterSet` and templates for the `ParameterSet` in each element of the array, the name and the comment that are displayed for the `ParameterSetContainer`s enclosing the `ParameterSet`s.
`ExpandableParameterSet(ParameterSet[] templateAndContent, String nameTemplate, String commentTemplate)` Creates a new `ExpandableParameterSet` from a `ParameterSet` -array.
`ExpandableParameterSet(ParameterSet template, String nameTemplate, String commentTemplate)` Creates a new `ExpandableParameterSet` from a `Class` that can be instantiated using this `ExpandableParameterSet` and templates for the `ParameterSet` in each element of the array, the name and the comment that are displayed for the `ParameterSetContainer`s enclosing the `ParameterSet`s.
`ExpandableParameterSet(ParameterSet template, String nameTemplate, String commentTemplate, int initCount)` Creates a new `ExpandableParameterSet` from a `Class` that can be instantiated using this `ExpandableParameterSet` and templates for the `ParameterSet` in each element of the array, the name and the comment that are displayed for the `ParameterSetContainer`s enclosing the `ParameterSet`s.
`MultiSelectionParameter(String name, String comment, boolean required, ParameterSet... values)` Creates a new `MultiSelectionParameter` from an array of `ParameterSet`s.
`ParameterSetContainer(ParameterSet p)` Creates an new `ParameterSetContainer` out of a `ParameterSet`.
`ParameterSetContainer(String name, String comment, ParameterSet content)` Creates an new `ParameterSetContainer` out of a `ParameterSet`.
`ParameterSetTagger(String[] tags, ParameterSet... sets)` The constructor creates an new instance by collecting and tagging all parameters of the `ParameterSet`s.
`SelectionParameter(String name, String comment, boolean required, ParameterSet... values)` Constructor for a `SelectionParameter` from an array of `ParameterSet`s.

Constructor parameters in de.jstacs.parameters with type arguments of type ParameterSet
`ParameterSetContainer(Class<? extends ParameterSet> contentClazz)` Creates an new `ParameterSetContainer` out of the class of a `ParameterSet`.
`ParameterSetContainer(String name, String comment, Class<? extends ParameterSet> contentClazz)` Creates an new `ParameterSetContainer` out of the class of a `ParameterSet`.

Uses of ParameterSet in de.jstacs.sampling

Subclasses of ParameterSet in de.jstacs.sampling
`class` | `AbstractBurnInTestParameterSet` Class for the parameters of a `AbstractBurnInTest`.
`class` | `VarianceRatioBurnInTestParameterSet` Class for the parameters of a `VarianceRatioBurnInTest`.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels
`class` | `BayesianNetworkDiffSMParameterSet` Class for the parameters of a `BayesianNetworkDiffSM`.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures
`static class` | `InhomogeneousMarkov.InhomogeneousMarkovParameterSet` Class for an `InstanceParameterSet` that defines the parameters of an `InhomogeneousMarkov` structure `Measure`.
`static class` | `Measure.MeasureParameterSet` This class is the super class of any `ParameterSet` that can be used to instantiate a `Measure`.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.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`.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.differentiable.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`.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete
`class` | `DGTrainSMParameterSet<T extends DiscreteGraphicalTrainSM>` The super `ParameterSet` for any parameter set of a `DiscreteGraphicalTrainSM`.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters
`class` | `HomMMParameterSet` This class implements a container for all parameters of a homogeneous Markov model.
`class` | `HomogeneousTrainSMParameterSet` This class implements a container for all parameters of any homogeneous model.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters
`class` | `BayesianNetworkTrainSMParameterSet` The `ParameterSet` for the class `BayesianNetworkTrainSM`.
`class` | `FSDAGModelForGibbsSamplingParameterSet` The class for the parameters of a `FSDAGModelForGibbsSampling`.
`class` | `FSDAGTrainSMParameterSet` The class for the parameters of a `FSDAGTrainSM` (fixed structure directed acyclic graphical model).
`class` | `IDGTrainSMParameterSet` This is the abstract container of parameters that is a root container for all inhomogeneous discrete graphical model parameter containers.

Uses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

Subclasses of ParameterSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
`class` | `BaumWelchParameterSet` This class implements an `HMMTrainingParameterSet` for the Baum-Welch training of an `AbstractHMM`.
`class` | `HMMTrainingParameterSet` This class implements an abstract `ParameterSet` that is used for the training of an `AbstractHMM`.
`class` | `MaxHMMTrainingParameterSet` This class is the super class for any `HMMTrainingParameterSet` that is used for a maximizing training algorithm of a hidden Markov model.
`class` | `MultiThreadedTrainingParameterSet` This class is the super class for any `MaxHMMTrainingParameterSet` that is used for a multi-threaded maximizing training algorithm of a hidden Markov model.
`class` | `NumericalHMMTrainingParameterSet` This class implements an `ParameterSet` for numerical training of an `AbstractHMM`.
`class` | `SamplingHMMTrainingParameterSet` This class contains the parameters for training training an `AbstractHMM` using a sampling strategy.
`class` | `ViterbiParameterSet` This class implements an `ParameterSet` for the viterbi training of an `AbstractHMM`.

Uses of ParameterSet in de.jstacs.utils

Method parameters in de.jstacs.utils with type arguments of type ParameterSet
`static
`<T> SelectionParameter`
` | `SubclassFinder.getSelectionParameter(Class<? extends ParameterSet> clazz, String startPackage, String name, String comment, boolean required)` This method creates an `SelectionParameter` that contains `InstanceParameterSet` for each possible class.

Uses of ParameterSet in de.jstacs.utils.galaxy

Constructors in de.jstacs.utils.galaxy with parameters of type ParameterSet
`GalaxyAdaptor(ParameterSet parameters, String toolname, String description, String version, String command)` Creates a new `GalaxyAdaptor` from a given `ParameterSet` containing all parameters that are necessary for a program is shall be included in a Galaxy installation.

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