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Packages that use Storable | |
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de.jstacs.classifier | This package provides the framework for any classifier. |
de.jstacs.classifier.assessment | This package allows to assess classifiers. |
de.jstacs.classifier.modelBased | Provides the classes for Classifier s that are based on Model s |
de.jstacs.classifier.scoringFunctionBased | Provides the classes for Classifier s that are based on ScoringFunction s. |
de.jstacs.classifier.scoringFunctionBased.cll | Provides the implementation of the log conditional likelihood as an OptimizableFunction and a classifier that uses log conditional likelihood or supervised posterior
to learn the parameters of a set of ScoringFunctions |
de.jstacs.classifier.scoringFunctionBased.logPrior | Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors |
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.data.sequences.annotation | Provides the facilities to annotate Sequence s using a number of pre-defined annotation types, or additional
implementations of the SequenceAnnotation class |
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.models | Provides the interface Model and its abstract implementation AbstractModel , which is the super class of all other models. |
de.jstacs.models.discrete | |
de.jstacs.models.discrete.inhomogeneous | This package contains various inhomogeneous models. |
de.jstacs.models.discrete.inhomogeneous.parameters | |
de.jstacs.models.discrete.inhomogeneous.shared | |
de.jstacs.models.mixture | This package is the super package for any mixture model. |
de.jstacs.models.mixture.gibbssampling | This package contains many classes that can be used while a Gibbs sampling. |
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.results | This package provides classes for results and sets of results. |
de.jstacs.scoringFunctions | Provides ScoringFunction s that can be used in a ScoreClassifier . |
de.jstacs.scoringFunctions.directedGraphicalModels | Provides ScoringFunction s that are equivalent to directed graphical models. |
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures | Provides the facilities to learn the structure of a BayesianNetworkScoringFunction . |
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures | Provides the facilities to learn the structure of a BayesianNetworkScoringFunction as
a Bayesian tree using a number of measures to define a rating of structures |
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures | Provides the facilities to learn the structure of a BayesianNetworkScoringFunction as
a permuted Markov model using a number of measures to define a rating of structures |
de.jstacs.scoringFunctions.homogeneous | Provides ScoringFunction s that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence |
de.jstacs.scoringFunctions.mix | Provides ScoringFunction s that are mixtures of other ScoringFunction s. |
Uses of Storable in de.jstacs.classifier |
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Classes in de.jstacs.classifier that implement Storable | |
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class |
AbstractClassifier
The super class for any classifier. |
class |
AbstractScoreBasedClassifier
This class is the main class for all score based classifiers. |
static class |
AbstractScoreBasedClassifier.DoubleTableResult
This class is for a table of double s. |
class |
ConfusionMatrix
This class holds the confusion matrix of a classifier. |
class |
MappingClassifier
This class allows the user to train the classifier on a given number of classes and to evaluate the classifier on a smaller number of classes by mapping classes together. |
class |
MeasureParameters
This class holds the parameters for evaluate-methods of a classifier. |
Uses of Storable in de.jstacs.classifier.assessment |
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Classes in de.jstacs.classifier.assessment that implement Storable | |
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class |
ClassifierAssessmentAssessParameterSet
This class is the super-class used by all ClassifierAssessmentAssessParameterSet s. |
class |
KFoldCVAssessParameterSet
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 RepatedHoldOutExperiment . |
class |
RepeatedSubSamplingAssessParameterSet
This class implements a ClassifierAssessmentAssessParameterSet that must be used
to call method assess() of a RepatedSubSamplingExperiment . |
class |
Sampled_RepeatedHoldOutAssessParameterSet
|
Uses of Storable in de.jstacs.classifier.modelBased |
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Classes in de.jstacs.classifier.modelBased that implement Storable | |
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class |
ModelBasedClassifier
This class is the main class for all model based classifiers. |
Uses of Storable in de.jstacs.classifier.scoringFunctionBased |
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Classes in de.jstacs.classifier.scoringFunctionBased that implement Storable | |
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class |
ScoreClassifier
|
class |
ScoreClassifierParameterSet
The parameter set for any CL classifier. |
Uses of Storable in de.jstacs.classifier.scoringFunctionBased.cll |
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Classes in de.jstacs.classifier.scoringFunctionBased.cll that implement Storable | |
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class |
CLLClassifier
This class implements the conditional log likelihood classifier. |
class |
CLLClassifierParameterSet
This class contains the parameters for the CLLClassifier . |
Uses of Storable in de.jstacs.classifier.scoringFunctionBased.logPrior |
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Classes in de.jstacs.classifier.scoringFunctionBased.logPrior that implement Storable | |
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class |
DoesNothingLogPrior
This class defines a LogPrior that does not penalize any parameter. |
class |
LogPrior
The abstract class for any log-prior used e.g. for maximum supervised posterior optimization. |
class |
SeparateGaussianLogPrior
Class for a LogPrior that defines a Gaussian prior on the parameters of a set of NormalizableScoringFunction s and a set of class-parameters. |
class |
SeparateLaplaceLogPrior
Class for a LogPrior that defines a Laplace-prior on the parameters of a set of NormalizableScoringFunction s and a set of class-parameters. |
class |
SeparateLogPrior
Abstract class for priors that penalize each parameter value independently and have some variance (and possible mean) as hyper-parameters. |
class |
SimpleGaussianSumLogPrior
This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter. |
Uses of Storable in de.jstacs.data |
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Classes in de.jstacs.data that implement Storable | |
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class |
Alphabet
Class for an Alphabet. |
static class |
Alphabet.AlphabetParameterSet
The super class for the ParameterSet of any Alphabet . |
class |
AlphabetContainer
The container for some alphabets used in a sequence, sample, model or ... . |
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
Class for the parameters of an array of Alphabet s where each alphabet may be used for one or more
sections of positions. |
Uses of Storable in de.jstacs.data.alphabets |
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Classes in de.jstacs.data.alphabets that implement Storable | |
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class |
ComplementableDiscreteAlphabet
This abstract class indicates that an alphabet can be used for to compute the complement. |
class |
ContinuousAlphabet
Class for a continuous alphabet. |
static class |
ContinuousAlphabet.ContinuousAlphabetParameterSet
Class for the ParameterSet of a ContinuousAlphabet . |
class |
DiscreteAlphabet
Class for an alphabet that consists of arbitrary Strings. |
static class |
DiscreteAlphabet.DiscreteAlphabetParameterSet
Class for the ParameterSet of a DiscreteAlphabet . |
class |
DNAAlphabet
This class implements the alphabet that is used for DNA. |
static class |
DNAAlphabet.DNAAlphabetParameterSet
The parameter set for an DNA alphabet. |
Uses of Storable in de.jstacs.data.sequences.annotation |
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Classes in de.jstacs.data.sequences.annotation that implement Storable | |
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class |
CisRegulatoryModuleAnnotation
Annotation for a cis-regulatory module as defined by a set of MotifAnnotation s of the motifs in the module. |
class |
IntronAnnotation
Annotation class for an intron as defined by a donor and an acceptor splice site. |
class |
LocatedSequenceAnnotation
Class for a SequenceAnnotation that has a position on the sequence, e.g for transcription start sites or intron-exon junctions. |
class |
LocatedSequenceAnnotationWithLength
Class for a SequenceAnnotation that has a position on the sequence and a length, e.g. for donor splice sites, exons, or genes. |
class |
MotifAnnotation
Class for a StrandedLocatedSequenceAnnotationWithLength that is a motif. |
class |
SequenceAnnotation
Class for a general annotation of a Sequence . |
class |
SinglePositionSequenceAnnotation
Class for some annotations that consist mainly of one position on a sequence. |
class |
StrandedLocatedSequenceAnnotationWithLength
Class for a SequenceAnnotation that has a position, a length, and an orientation on the strand of a Sequence . |
Uses of Storable in de.jstacs.io |
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Methods in de.jstacs.io that return Storable | |
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static Storable[][] |
XMLParser.extractStorable2ArrayForTag(StringBuffer source,
String tag)
Returns the value between equal start and end tags as a two dimensional Storable array. |
static Storable[][] |
XMLParser.extractStorable2ArrayForTag(StringBuffer source,
String startTag,
String endTag)
Returns the value between start and end tag as a two dimensional Storable array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayForTag(StringBuffer source,
String tag)
Returns the value between equal start and end tags as a three dimensional Storable array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayForTag(StringBuffer source,
String startTag,
String endTag)
Returns the value between start and end tag as a three dimensional Storable array. |
static Storable[] |
XMLParser.extractStorableArrayForTag(StringBuffer source,
String startTag)
Returns the value between equal start and end tags as a Storable array. |
static Storable[] |
XMLParser.extractStorableArrayForTag(StringBuffer source,
String startTag,
String endTag)
Returns the value between start and end tag as a Storable array. |
static Storable |
XMLParser.extractStorableForTag(StringBuffer source,
String startTag)
Returns the value between equal start and end tags as Storable . |
static Storable |
XMLParser.extractStorableForTag(StringBuffer source,
String startTag,
String endTag)
Returns the value between start and end tag as Storable . |
static Storable |
XMLParser.extractStorableOrNullForTag(StringBuffer source,
String tag)
Returns the value between equal start and end tags as Storable or null . |
static Storable |
XMLParser.extractStorableOrNullForTag(StringBuffer source,
String startTag,
String endTag)
Returns the value between start and end tag as Storable or null . |
Methods in de.jstacs.io with parameters of type Storable | |
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static void |
XMLParser.appendStorable2ArrayWithTags(StringBuffer source,
Storable[][] s,
String tag)
Appends an encoded two dimensional Storable array with equal tags to the StringBuffer source . |
static void |
XMLParser.appendStorable2ArrayWithTags(StringBuffer source,
Storable[][] s,
String startTag,
String endTag)
Appends an encoded two dimensional Storable array with start and end tag to the StringBuffer source . |
static void |
XMLParser.appendStorable3ArrayWithTags(StringBuffer source,
Storable[][][] s,
String tag)
Appends an encoded three dimensional Storable array with equal tags to the StringBuffer source . |
static void |
XMLParser.appendStorable3ArrayWithTags(StringBuffer source,
Storable[][][] s,
String startTag,
String endTag)
Appends an encoded three dimensional Storable array with start and end tag to the StringBuffer source . |
static void |
XMLParser.appendStorableArrayWithTags(StringBuffer source,
Storable[] s,
String tag)
Appends an encoded Storable array with equal tags to the StringBuffer source . |
static void |
XMLParser.appendStorableArrayWithTags(StringBuffer source,
Storable[] s,
String startTag,
String endTag)
Appends an encoded Storable array with start and end tag to the StringBuffer source . |
static void |
XMLParser.appendStorableOrNullWithTags(StringBuffer source,
Storable s,
String tag)
Appends a Storable object or "null" with equal tags to the StringBuffer source . |
static void |
XMLParser.appendStorableOrNullWithTags(StringBuffer source,
Storable s,
String startTag,
String endTag)
Appends a Storable object or "null" with start and end tag to the StringBuffer source . |
static void |
XMLParser.appendStorableWithTags(StringBuffer source,
Storable s,
String startTag)
Appends a Storable object with equal tags to the StringBuffer source . |
static void |
XMLParser.appendStorableWithTags(StringBuffer source,
Storable s,
String startTag,
String endTag)
Appends a Storable object with start and end tag to the StringBuffer source . |
protected static StringBuffer |
XMLParser.StorableArrayWithTags(Storable[] s)
Encodes a Storable array. |
Uses of Storable in de.jstacs.models |
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Subinterfaces of Storable in de.jstacs.models | |
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interface |
Model
This interface defines all methods for a probabilistic model. |
Classes in de.jstacs.models that implement Storable | |
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class |
AbstractModel
Abstract class for a model for pattern recognition. |
class |
CompositeModel
This class is for modelling sequences by modelling the different positions of the each sequence by different models. |
class |
UniformModel
This class represents an uniform model. |
Uses of Storable in de.jstacs.models.discrete |
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Classes in de.jstacs.models.discrete that implement Storable | |
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class |
Constraint
The main class for all constraints on models. |
class |
DGMParameterSet
The super ParameterSet for any ParameterSet of a DiscreteGraphicalModel . |
class |
DiscreteGraphicalModel
This is the main class for all discrete graphical models (DGM) |
Uses of Storable in de.jstacs.models.discrete.inhomogeneous |
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Classes in de.jstacs.models.discrete.inhomogeneous that implement Storable | |
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class |
BayesianNetworkModel
The class implements a Bayesian network of fixed order. |
class |
DAGModel
The abstract class for directed acyclic graphical models. |
class |
FSDAGModel
This class can be used for any discrete fixed structure DAG model (FSDAGModel). |
class |
InhCondProb
This class handles the (conditional) probabilities. |
class |
InhConstraint
This class is the super class for all inhomogeneous constraints. |
class |
InhomogeneousDGM
This class is the main class for all inhomgeneous discrete graphical models (IDGM). |
class |
MEMConstraint
The constraint can be used for any MEM application. |
Uses of Storable in de.jstacs.models.discrete.inhomogeneous.parameters |
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Classes in de.jstacs.models.discrete.inhomogeneous.parameters that implement Storable | |
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class |
BayesianNetworkModelParameterSet
The ParameterSet for the class BayesianNetworkModel. |
class |
FSDAGMParameterSet
The class for the parameters of a FSDAGModel. |
class |
IDGMParameterSet
This is the abstract container of parameters that is root container for all inhomogeneous discrete graphical model parameter containers. |
Uses of Storable in de.jstacs.models.discrete.inhomogeneous.shared |
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Classes in de.jstacs.models.discrete.inhomogeneous.shared that implement Storable | |
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class |
SharedStructureClassifier
This class enables you to learn the structure on all classes together. |
class |
SharedStructureMixture
This class handles a mixture of models with the same structure that are learned via EM. |
Uses of Storable in de.jstacs.models.mixture |
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Classes in de.jstacs.models.mixture that implement Storable | |
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class |
AbstractMixtureModel
This is the abstract class for all kinds of mixture models. |
class |
MixtureModel
Class for a mixture model of any Model s. |
class |
StrandModel
This model handles sequences that can either lie on the forward strand or on the backward strand. |
Uses of Storable in de.jstacs.models.mixture.gibbssampling |
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Classes in de.jstacs.models.mixture.gibbssampling that implement Storable | |
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class |
BurnInTest
This is the abstract super class for any test of the length of the burn-in phase. |
class |
FSDAGModelForGibbsSampling
This is the class for a fixed structure directed acyclic graphical model that can be used in a Gibbs sampling. |
class |
SimpleBurnInTest
This is a very simple test for the length of the burn-in phase. |
Uses of Storable in de.jstacs.parameters |
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Classes in de.jstacs.parameters that implement Storable | |
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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 |
CollectionParameter
Class for a collection parameter, i.e. a parameter that provides some collection of possible values the user can choose from. |
class |
EnumParameter
This class implements a CollectionParameter 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. |
static class |
FileParameter.FileRepresentation
Class that represents a file |
class |
InstanceParameterSet
Abstract class for a ParameterSet containing all parameters necessary to construct an
Object that implements InstantiableFromParameterSet . |
class |
MultiSelectionCollectionParameter
Class for a Parameter that provides a collection of possible values. |
class |
Parameter
Abstract class for a parameter that shall be used as the parameter of some method, constructor, etc. |
class |
ParameterSet
(Container) class for a set of Parameter s. |
class |
ParameterSetContainer
Class for a Parameter 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. |
class |
SimpleParameter
Class for a "simple" parameter. |
class |
SimpleParameterSet
Class for a ParameterSet that is constructed from an array of Parameters
and thus does nothing in the loadParameters() -method. |
Uses of Storable in de.jstacs.parameters.validation |
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Subinterfaces of Storable in de.jstacs.parameters.validation | |
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interface |
Constraint
Interface for a constraint that must be fulfilled in a ConstraintValidator |
interface |
ParameterValidator
Interface for a parameter validator, i.e. a class that can validate some possible parameter value. |
Classes in de.jstacs.parameters.validation that implement Storable | |
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class |
ConstraintValidator
Class for a ParameterValidator that is based on Constraint s. |
class |
NumberValidator<E extends Comparable<? extends Number>>
Class that validates all subclasses of Number that implement Comparable (e.g. |
class |
ReferenceConstraint
Class for a Constraint that defines a condition on one Parameter (the one containing
the ConstraintValidator ) with respect to another Parameter . |
class |
SimpleReferenceConstraint
Class for a ReferenceConstraint that checks for "simple" conditions as defined
in the Constraint -interface. |
class |
SimpleStaticConstraint
Class for a Constraint that checks values against static values using the comparison operators
defined in the Constraint -interface. |
class |
StorableValidator
Class for a validator that validates instances and XML-representations for the correct class types (e.g. |
Constructor parameters in de.jstacs.parameters.validation with type arguments of type Storable | |
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StorableValidator(Class<? extends Storable> clazz)
Creates a new ObjectValidator for a subclass of Storable . |
|
StorableValidator(Class<? extends Storable> clazz,
boolean trained)
Creates a new ObjectValidator for a subclass of AbstractModel
or AbstractClassifier . |
Uses of Storable in de.jstacs.results |
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Classes in de.jstacs.results that implement Storable | |
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class |
CategoricalResult
A class for categorical results (i.e. non-numerical results) for primitives and Strings |
class |
ImageResult
A class for results that are images of the PNG format. |
class |
ListResult
Class for a Result that contains a list or a matrix, respectively, of ResultSet s. |
class |
MeanResultSet
Class that computes the mean and the standard error of a series of NumericalResultSet s. |
class |
NumericalResult
Class for numerical Result values. |
class |
NumericalResultSet
Class for a set of numerical result values, which are all of the type NumericalResult . |
class |
Result
The abstract class for any result. |
class |
ResultSet
Class for a set of Result s, which provides methods to access single Result s in the set, to retrieve
the number of Result s in the set, to get a String representation or an XML-representation of all the Result s
in the set. |
class |
SampleResult
Result that contains a Sample . |
class |
SimpleResult
Abstract class for a Result with a value of a primitive data type or String . |
class |
StorableResult
Class for results that are Storable s. |
Methods in de.jstacs.results that return Storable | |
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Storable |
StorableResult.getResultInstance()
Returns the instance of the Storable that is the result of
this ObjectResult |
Constructors in de.jstacs.results with parameters of type Storable | |
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StorableResult(String name,
String comment,
Storable object)
Creates a result for an XML-representation of an object. |
Uses of Storable in de.jstacs.scoringFunctions |
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Subinterfaces of Storable in de.jstacs.scoringFunctions | |
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interface |
NormalizableScoringFunction
The interface for normalizable ScoringFunctions. |
interface |
ScoringFunction
This interface is the main part of any ScoreClassifier. |
Classes in de.jstacs.scoringFunctions that implement Storable | |
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class |
AbstractNormalizableScoringFunction
This class is the main part of any ScoreClassifier. |
class |
IndependentProductScoringFunction
This class enables the user to model parts of the sequence independent of each other. |
class |
MRFScoringFunction
This class implements the scoring function for any MRF. |
class |
UniformScoringFunction
This scoring function does nothing. |
class |
VariableLengthScoringFunction
This is the main class for all ScoringFunctions that allow to score subsequences of arbitrary length. |
Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels |
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Classes in de.jstacs.scoringFunctions.directedGraphicalModels that implement Storable | |
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class |
BayesianNetworkScoringFunction
This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network. |
Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures |
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Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures that implement Storable | |
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class |
InhomogeneousMarkov
Class for a network structure of a BayesianNetworkScoringFunction that is an inhomogeneous Markov model. |
class |
Measure
Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data. |
Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures |
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Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures that implement Storable | |
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class |
BTExplainingAwayResidual
Structure learning Measure that computes a maximum spanning tree based on the explaining away residual and uses the resulting
tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a BayesianNetworkScoringFunction . |
class |
BTMutualInformation
Structure learning Measure that computes a maximum spanning tree based on mutual information and uses the resulting
tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a BayesianNetworkScoringFunction . |
Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures |
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Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures that implement Storable | |
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class |
PMMExplainingAwayResidual
Class for the network structure of a BayesianNetworkScoringFunction that is a permuted Markov model based on the explaining away residual. |
class |
PMMMutualInformation
Class for the network structure of a BayesianNetworkScoringFunction that is a permuted Markov model based on mutual information. |
Uses of Storable in de.jstacs.scoringFunctions.homogeneous |
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Classes in de.jstacs.scoringFunctions.homogeneous that implement Storable | |
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class |
HMM0ScoringFunction
This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length. |
class |
HMMScoringFunction
This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length. |
class |
HomogeneousScoringFunction
This is the main class for all homogeneous ScoringFunctions. |
class |
UniformHomogeneousScoringFunction
This scoring function does nothing. |
Uses of Storable in de.jstacs.scoringFunctions.mix |
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Classes in de.jstacs.scoringFunctions.mix that implement Storable | |
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class |
AbstractMixtureScoringFunction
This main abstract class for any mixture (e.g. |
class |
MixtureScoringFunction
This class implements a real mixture model. |
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