Uses of Interface
de.jstacs.parameters.GalaxyConvertible

Packages that use GalaxyConvertible

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 Classifiers that are based on SequenceScores.
de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix	Provides an implementation of a classifier that allows to train the parameters of a set of DifferentiableStatisticalModels by a unified generative-discriminative learning principle
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling	Provides the classes for AbstractScoreBasedClassifiers that are based on SamplingDifferentiableStatisticalModels 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.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.sampling	This package contains many classes that can be used while a sampling.
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels	Provides DifferentiableStatisticalModels 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

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

Classes in de.jstacs.algorithms.optimization.termination that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.classifiers.assessment

Classes in de.jstacs.classifiers.assessment that implement GalaxyConvertible

class	ClassifierAssessmentAssessParameterSet This class is the superclass used by all ClassifierAssessmentAssessParameterSets.
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 GalaxyConvertible in de.jstacs.classifiers.differentiableSequenceScoreBased

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased that implement GalaxyConvertible

class

ScoreClassifierParameterSet A set of Parameters for any ScoreClassifier.

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

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix that implement GalaxyConvertible

class

GenDisMixClassifierParameterSet This class contains the parameters for the GenDisMixClassifier.

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

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling that implement GalaxyConvertible

class	SamplingGenDisMixClassifierParameterSet ParameterSet to instantiate a SamplingGenDisMixClassifier.
class	SamplingScoreBasedClassifierParameterSet ParameterSet to instantiate a SamplingScoreBasedClassifier.

Uses of GalaxyConvertible in de.jstacs.classifiers.performanceMeasures

Classes in de.jstacs.classifiers.performanceMeasures that implement GalaxyConvertible

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 NumericalPerformanceMeasures that can be used, for instance, in an repeated assessment, (cf.
class	PerformanceMeasureParameterSet This class implements a container of AbstractPerformanceMeasures 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 GalaxyConvertible in de.jstacs.data

Classes in de.jstacs.data that implement GalaxyConvertible

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 Alphabets of defined length.
static class	AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet Class for the parameter set of an array of Alphabets where each Alphabet may be used for one or more sections of positions.

Uses of GalaxyConvertible in de.jstacs.data.alphabets

Classes in de.jstacs.data.alphabets that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.parameters

Classes in de.jstacs.parameters that implement GalaxyConvertible

class	AbstractSelectionParameter Class for a collection parameter, i.e. a parameter that provides some collection of possible values the user can choose from.
class	ArrayParameterSet Class for a ParameterSet that consists of a length-Parameter that defines the length of the array and an array of ParameterSetContainers of this length.
class	EnumParameter This class implements a SelectionParameter based on an Enum.
class	ExpandableParameterSet A class for a ParameterSet that can be expanded by additional Parameters at runtime.
class	FileParameter Class for a Parameter that represents a local file.
class	InstanceParameterSet<T extends InstantiableFromParameterSet> Container class for a set of Parameters that can be used to instantiate another class.
class	MultiSelectionParameter Class for a Parameter that provides a collection of possible values.
class	ParameterSet (Container) class for a set of Parameters.
class	ParameterSetContainer Class for a ParameterSetContainer that contains a ParameterSet as value.
class	RangeParameter Class for a parameter wrapper that allows SimpleParameters to be set to a set of values.
class	SelectionParameter Class for a collection parameter, i.e. a parameter that provides some collection of possible values the user can choose from.
class	SequenceScoringParameterSet<T extends InstantiableFromParameterSet> Abstract class for a ParameterSet containing all parameters necessary to construct an Object that implements InstantiableFromParameterSet.
class	SimpleParameter Class for a "simple" parameter.
class	SimpleParameterSet Class for a ParameterSet that is constructed from an array of Parameters.

Uses of GalaxyConvertible in de.jstacs.parameters.validation

Classes in de.jstacs.parameters.validation that implement GalaxyConvertible

class

NumberValidator<E extends Comparable<? extends Number>> Class that validates all subclasses of Number that implement Comparable (e.g.

Uses of GalaxyConvertible in de.jstacs.sampling

Classes in de.jstacs.sampling that implement GalaxyConvertible

class	AbstractBurnInTestParameterSet Class for the parameters of a AbstractBurnInTest.
class	VarianceRatioBurnInTestParameterSet Class for the parameters of a VarianceRatioBurnInTest.

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

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels that implement GalaxyConvertible

class

BayesianNetworkDiffSMParameterSet Class for the parameters of a BayesianNetworkDiffSM.

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

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.btMeasures that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures

Classes in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.sequenceScores.statisticalModels.trainable.discrete

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete that implement GalaxyConvertible

class

DGTrainSMParameterSet<T extends DiscreteGraphicalTrainSM> The super ParameterSet for any parameter set of a DiscreteGraphicalTrainSM.

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

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.parameters that implement GalaxyConvertible

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 GalaxyConvertible in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training that implement GalaxyConvertible

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.