Uses of Class
de.jstacs.io.ParameterSetParser.NotInstantiableException

Packages that use ParameterSetParser.NotInstantiableException

de.jstacs.classifiers.differentiableSequenceScoreBased	Provides the classes for Classifiers that are based on SequenceScores. It includes a sub-package for discriminative objective functions, namely conditional likelihood and supervised posterior, and a separate sub-package for the parameter priors, that can be used for the supervised posterior.
de.jstacs.data	Provides classes for the representation of data. The base classes to represent data are Alphabet and AlphabetContainer for representing alphabets, Sequence and its sub-classes to represent continuous and discrete sequences, and DataSet to represent data sets comprising a set of 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 Storables 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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels	Provides DifferentiableStatisticalModels that are directed graphical models.
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 ParameterSetParser.NotInstantiableException in de.jstacs.classifiers.differentiableSequenceScoreBased

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased that throw ParameterSetParser.NotInstantiableException

AbstractTerminationCondition

ScoreClassifierParameterSet.getTerminantionCondition() This method returns the AbstractTerminationCondition for stopping the training, e.g., if the difference of the scores between two iterations is smaller than a given threshold the training is stopped.

Uses of ParameterSetParser.NotInstantiableException in de.jstacs.data

Constructors in de.jstacs.data that throw ParameterSetParser.NotInstantiableException

AlphabetContainer(AlphabetContainerParameterSet parameters)
Creates a new AlphabetContainer from an AlphabetContainerParameterSet that contains all necessary parameters.

Uses of ParameterSetParser.NotInstantiableException in de.jstacs.io

Methods in de.jstacs.io that throw ParameterSetParser.NotInstantiableException

static <T extends InstantiableFromParameterSet> T	ParameterSetParser.getInstanceFromParameterSet(InstanceParameterSet<T> pars) Returns an instance of a subclass of InstantiableFromParameterSet that can be instantiated by the InstanceParameterSet pars.
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 ParameterSetParser.NotInstantiableException in de.jstacs.parameters

Methods in de.jstacs.parameters that throw ParameterSetParser.NotInstantiableException

T	InstanceParameterSet.getInstance() Returns a new instance of the class of InstanceParameterSet.getInstanceClass() that was created using this ParameterSet.

Uses of ParameterSetParser.NotInstantiableException in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels that throw ParameterSetParser.NotInstantiableException

Measure

BayesianNetworkDiffSMParameterSet.getMeasure() Returns the structure Measure defined by this set of parameters.

Constructors in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels that throw ParameterSetParser.NotInstantiableException

BayesianNetworkDiffSM(BayesianNetworkDiffSMParameterSet parameters)
Creates a new BayesianNetworkDiffSM that has neither been initialized nor trained from a BayesianNetworkDiffSMParameterSet.

Uses of ParameterSetParser.NotInstantiableException in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training that throw ParameterSetParser.NotInstantiableException

AbstractBurnInTest	SamplingHMMTrainingParameterSet.getBurnInTest() This method return the burn in test to be used during sampling.
AbstractTerminationCondition	MaxHMMTrainingParameterSet.getTerminationCondition() This method returns the AbstractTerminationCondition for stopping the training, e.g., if the difference of the scores between two iterations is smaller than a given threshold the training is stopped.