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.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.tools | |
de.jstacs.tools.ui.galaxy | |
de.jstacs.utils |
This package contains a bundle of useful classes and interfaces like ...
|
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 | Method and Description |
---|---|
static <T extends InstantiableFromParameterSet> |
ParameterSetParser.getInstanceFromParameterSet(ParameterSet pars,
Class<T> instanceClass)
Returns an instance of a subclass of
InstantiableFromParameterSet
that can be instantiated by the ParameterSet pars . |
Modifier and Type | Class and Description |
---|---|
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. |
Modifier and Type | Field and Description |
---|---|
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 |
Modifier and Type | Method and Description |
---|---|
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() |
Modifier and Type | Method and Description |
---|---|
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. |
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)
|
Modifier and Type | Method and Description |
---|---|
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.
|
Constructor and Description |
---|
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 and Description |
---|
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 . |
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 | Method and Description |
---|---|
ParameterSet |
ToolResult.getToolParameters()
Returns the tool's parameters that have been used to create the results stored in this
ToolResult . |
ParameterSet |
JstacsTool.getToolParameters()
Returns the input parameters of this tool.
|
Modifier and Type | Method and Description |
---|---|
static FileParameter |
DataColumnParameter.find(ParameterSet top,
String dataRef)
Finds the parameter for the given ID in a
ParameterSet . |
ToolResult |
JstacsTool.run(ParameterSet parameters,
Protocol protocol,
ProgressUpdater progress,
int threads)
Runs the tool using the provided (now filled) parameters, which are in structure identical to those returned by
JstacsTool.getToolParameters() . |
void |
ToolResult.setFromStoredParameters(ParameterSet other)
Sets the values of all parameters in
other to those stored in the internal parameters
that have been supplied upon construction. |
Constructor and Description |
---|
ToolResult(String name,
String comment,
ResultSet annotation,
ResultSet result,
ParameterSet toolParameters,
String toolName,
Date finished)
Creates a new
ToolResult with most arguments identical to those of a ListResult . |
Constructor and Description |
---|
GalaxyAdaptor(ParameterSet parameters,
JstacsTool.ResultEntry[] defaultResults,
boolean[] addLine,
String toolname,
String description,
String version,
String command,
String labelName)
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. |
Modifier and Type | Method and Description |
---|---|
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. |