Package | Description |
---|---|
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.
It contains the class ClassifierAssessment that
is used as a super-class of all implemented methodologies of
an assessment to assess classifiers. |
de.jstacs.classifiers.differentiableSequenceScoreBased |
Provides the classes for
Classifier s that are based on SequenceScore s.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.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.
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.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
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.tools | |
de.jstacs.tools.ui.galaxy |
Modifier and Type | Class and Description |
---|---|
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( ...
|
class |
RepeatedHoldOutAssessParameterSet
This class implements a ClassifierAssessmentAssessParameterSet that
must be used to call method assess( ...
|
class |
RepeatedSubSamplingAssessParameterSet
This class implements a ClassifierAssessmentAssessParameterSet that
must be used to call method assess( ...
|
class |
Sampled_RepeatedHoldOutAssessParameterSet
This class implements a ClassifierAssessmentAssessParameterSet that
must be used to call the method assess( ...
|
Modifier and Type | Class and Description |
---|---|
class |
ScoreClassifierParameterSet
A set of
Parameter s for any
ScoreClassifier . |
Modifier and Type | Class and Description |
---|---|
class |
GenDisMixClassifierParameterSet
This class contains the parameters for the
GenDisMixClassifier . |
Modifier and Type | Class and Description |
---|---|
class |
SamplingGenDisMixClassifierParameterSet
ParameterSet to instantiate a SamplingGenDisMixClassifier . |
class |
SamplingScoreBasedClassifierParameterSet
ParameterSet to instantiate a SamplingScoreBasedClassifier . |
Modifier and Type | Class and Description |
---|---|
class |
AbstractNumericalTwoClassPerformanceMeasure
This class is the abstract super class of any performance measure that can only be computed for binary classifiers.
|
class |
AbstractPerformanceMeasure
This class is the abstract super class of any performance measure used to evaluate
an
AbstractClassifier . |
class |
AbstractPerformanceMeasureParameterSet<T extends PerformanceMeasure>
This class implements a container of
PerformanceMeasure s that can be used
in AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...) . |
class |
AbstractTwoClassPerformanceMeasure
This class is the abstract super class of any performance measure that can only be computed for binary classifiers.
|
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 |
CorrelationCoefficient
PerformanceMeasure using Pearson or Spearman correlation between prediction scores and
weighted class labels. |
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(AbstractPerformanceMeasureParameterSet, 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.
|
Modifier and Type | Class and Description |
---|---|
static class |
AlphabetContainer.AbstractAlphabetContainerParameterSet<T extends AlphabetContainer>
This class is the super class of any
InstanceParameterSet for AlphabetContainer . |
class |
AlphabetContainerParameterSet
Class for the
ParameterSet of an AlphabetContainer . |
static class |
AlphabetContainerParameterSet.AlphabetArrayParameterSet
Class for the parameters of an array of
Alphabet s of defined
length. |
static class |
AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractSelectionParameter
Class for a collection parameter, i.e.
|
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 |
EnumParameter
This class implements a
SelectionParameter based on an Enum . |
class |
ExpandableParameterSet
A class for a
ParameterSet that can be expanded by additional
Parameter s at runtime. |
class |
FileParameter
Class for a
Parameter that represents a local file. |
class |
InstanceParameterSet<T extends InstantiableFromParameterSet>
Container class for a set of
Parameter s 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
Parameter s. |
class |
ParameterSetContainer
Class for a
ParameterSetContainer that contains a
ParameterSet as value. |
class |
RangeParameter
Class for a parameter wrapper that allows
SimpleParameter s to be set
to a set of values.These values may be given either as a list of values separated by spaces, as a range between a first and a last value with a given number of steps between these values, or a single value. |
class |
SelectionParameter
Class for a collection parameter, i.e.
|
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 Parameter s. |
Modifier and Type | Class and Description |
---|---|
class |
NumberValidator<E extends Comparable<? extends Number>>
Class that validates all subclasses of
Number that implement
Comparable (e.g. |
class |
RegExpValidator
ParameterValidator that checks if a given input String matches a regular expression. |
Modifier and Type | Class and Description |
---|---|
class |
AbstractBurnInTestParameterSet
Class for the parameters of a
AbstractBurnInTest . |
class |
VarianceRatioBurnInTestParameterSet
Class for the parameters of a
VarianceRatioBurnInTest . |
Modifier and Type | Class and Description |
---|---|
class |
BayesianNetworkDiffSMParameterSet
Class for the parameters of a
BayesianNetworkDiffSM . |
Modifier and Type | Class and Description |
---|---|
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 . |
Modifier and Type | Class and Description |
---|---|
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 . |
Modifier and Type | Class and Description |
---|---|
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 . |
Modifier and Type | Class and Description |
---|---|
class |
DGTrainSMParameterSet<T extends DiscreteGraphicalTrainSM>
The super
ParameterSet for any parameter set of
a DiscreteGraphicalTrainSM . |
Modifier and Type | Class and Description |
---|---|
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.
|
Modifier and Type | Class and Description |
---|---|
class |
BayesianNetworkTrainSMParameterSet
The
ParameterSet for the class
BayesianNetworkTrainSM . |
class |
ConstraintParameterSet
This class enables you to input your own structure defined by some constraints.
|
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 |
FSMEMParameterSet
The ParameterSet for a FSMEManager.
|
class |
IDGTrainSMParameterSet
This is the abstract container of parameters that is a root container for all
inhomogeneous discrete graphical model parameter containers.
|
class |
MEManagerParameterSet
The ParameterSet for any MEManager.
|
Modifier and Type | Class and Description |
---|---|
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 . |
Modifier and Type | Class and Description |
---|---|
class |
DataColumnParameter
SimpleParameter that represents a data column parameter in Galaxy and JstacsFX. |
Modifier and Type | Class and Description |
---|---|
class |
MultilineSimpleParameter
An extension of
SimpleParameter that renders as a textarea in Galaxy, which is only suitable for DataType.STRING s. |