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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.gendismix | Provides an implementation of a classifier that allows to train the parameters of a set of NormalizableScoringFunction s by
a unified generative-discriminative learning principle |
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.classifier.scoringFunctionBased.msp | Provides an implementation of a classifier that allows to train the parameters of a set of ScoringFunctions either
by maximum supervised posterior (MSP) or by maximum conditional likelihood (MCL) |
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.homogeneous | |
de.jstacs.models.discrete.homogeneous.parameters | |
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.models.mixture.motif | |
de.jstacs.models.mixture.motif.positionprior | |
de.jstacs.motifDiscovery | This package provides the framework including the interface for any de novo motif discoverer |
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. |
de.jstacs.scoringFunctions.mix.motifSearch | |
de.jstacs.utils | This package contains a bundle of useful classes and interfaces like ... |
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 Result s given as 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 the 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 superclass 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
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 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
This abstract class implements the main functionality of a ScoringFunction based classifier. |
class |
ScoreClassifierParameterSet
A set of Parameter s for any
ScoreClassifier . |
Uses of Storable in de.jstacs.classifier.scoringFunctionBased.gendismix |
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Classes in de.jstacs.classifier.scoringFunctionBased.gendismix that implement Storable | |
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class |
GenDisMixClassifier
This class implements a classifier the optimizes the following function ![]() |
class |
GenDisMixClassifierParameterSet
This class contains the parameters for the GenDisMixClassifier . |
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 |
CompositeLogPrior
This class implements a composite prior that can be used for NormalizableScoringFunction. |
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 variances (and possible means) as hyperparameters. |
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.classifier.scoringFunctionBased.msp |
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Classes in de.jstacs.classifier.scoringFunctionBased.msp that implement Storable | |
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class |
MSPClassifier
This class implements a classifier that allows the training via MCL or MSP principle. |
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 a set of symbols, i.e. an Alphabet . |
static class |
Alphabet.AlphabetParameterSet
The super class for the InstanceParameterSet of any
Alphabet . |
class |
AlphabetContainer
The container for Alphabet s used in a Sequence ,
Sample , AbstractModel or ... . |
class |
AlphabetContainerParameterSet
Class for the AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet 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 parameter set 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 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 String s. |
static class |
DiscreteAlphabet.DiscreteAlphabetParameterSet
Class for the ParameterSet of a
DiscreteAlphabet . |
class |
DNAAlphabet
This class implements the discrete alphabet that is used for DNA. |
static class |
DNAAlphabet.DNAAlphabetParameterSet
The parameter set for a DNAAlphabet . |
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.extractStorable2ArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes)
Returns the value between the tags as two dimensional Storable array. |
static Storable[][] |
XMLParser.extractStorable2ArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as two dimensional Storable
array. |
static Storable[][] |
XMLParser.extractStorable2ArrayForTag(StringBuffer source,
String tag)
Returns the value between the tags as two dimensional Storable array. |
static Storable[][] |
XMLParser.extractStorable2ArrayForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as two dimensional Storable
array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes)
Returns the value between the tags as three dimensional Storable array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as three dimensional Storable array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayForTag(StringBuffer source,
String tag)
Returns the value between the tags as three dimensional Storable array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as three dimensional Storable array. |
static Storable |
XMLParser.extractStorableAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes)
Returns the value between the tags as Storable or null . |
static Storable |
XMLParser.extractStorableAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable or null . |
static Storable[] |
XMLParser.extractStorableArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes)
Returns the value between the tags as Storable array. |
static Storable[] |
XMLParser.extractStorableArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable array. |
static Storable[] |
XMLParser.extractStorableArrayForTag(StringBuffer source,
String tag)
Returns the value between the tags as Storable array. |
static Storable[] |
XMLParser.extractStorableArrayForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable array. |
static Storable |
XMLParser.extractStorableForTag(StringBuffer source,
String tag)
Returns the value between the tags as Storable or null . |
static Storable |
XMLParser.extractStorableForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags 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.appendStorable2ArrayWithTagsAndAttributes(StringBuffer source,
Storable[][] s,
String tag,
String attributes)
Appends an encoded two dimensional Storable array with the
tags 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.appendStorable3ArrayWithTagsAndAttributes(StringBuffer source,
Storable[][][] s,
String tag,
String attributes)
Appends an encoded three dimensional Storable array with the
tags 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.appendStorableArrayWithTagsAndAttributes(StringBuffer source,
Storable[] s,
String tag,
String attributes)
Appends an encoded Storable array with the tags to the
StringBuffer source . |
static void |
XMLParser.appendStorableWithTags(StringBuffer source,
Storable s,
String tag)
Appends a Storable object or "null" with equal tags to
the StringBuffer source . |
static void |
XMLParser.appendStorableWithTagsAndAttributes(StringBuffer source,
Storable s,
String tag,
String attributes)
Appends a Storable object or "null" with the
tags to the StringBuffer source . |
protected static StringBuffer |
XMLParser.getStorableArrayWithTags(Storable[] s)
Encodes a Storable array. |
Method parameters in de.jstacs.io with type arguments of type Storable | |
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static Storable[][] |
XMLParser.extractStorable2ArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as two dimensional Storable
array. |
static Storable[][] |
XMLParser.extractStorable2ArrayForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as two dimensional Storable
array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as three dimensional Storable array. |
static Storable[][][] |
XMLParser.extractStorable3ArrayForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as three dimensional Storable array. |
static Storable |
XMLParser.extractStorableAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable or null . |
static Storable[] |
XMLParser.extractStorableArrayAndAttributesForTag(StringBuffer source,
String tag,
Map<String,String> attributes,
Map<String,String> filterAttributes,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable array. |
static Storable[] |
XMLParser.extractStorableArrayForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable array. |
static Storable |
XMLParser.extractStorableForTag(StringBuffer source,
String tag,
Class<? extends Storable> clazz)
Returns the value between the tags as Storable or null . |
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 |
NormalizableScoringFunctionModel
This model can be used to use a NormalizableScoringFunction as model. |
class |
UniformModel
This class represents a uniform model. |
class |
VariableLengthWrapperModel
This class allows to train any Model on Sample s of Sequence s with
variable length if each individual length is at least Model.getLength() . |
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 parameter set of
a DiscreteGraphicalModel . |
class |
DiscreteGraphicalModel
This is the main class for all discrete graphical models (DGM). |
Uses of Storable in de.jstacs.models.discrete.homogeneous |
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Classes in de.jstacs.models.discrete.homogeneous that implement Storable | |
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class |
HomogeneousMM
This class implements homogeneous Markov models (hMM) of arbitrary order. |
class |
HomogeneousModel
This class implements homogeneous models of arbitrary order. |
protected class |
HomogeneousModel.HomCondProb
This class handles the (conditional) probabilities of a homogeneous model in a fast way. |
Uses of Storable in de.jstacs.models.discrete.homogeneous.parameters |
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Classes in de.jstacs.models.discrete.homogeneous.parameters that implement Storable | |
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class |
HomMMParameterSet
This class implements a container for all parameters of a homogeneous Markov model. |
class |
HomogeneousModelParameterSet
This class implements a container for all parameters of any homogeneous model. |
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 ( StructureLearner.ModelType.BN ) of fixed order. |
class |
DAGModel
The abstract class for directed acyclic graphical models ( DAGModel ). |
class |
FSDAGModel
This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGModel ). |
class |
InhCondProb
This class handles (conditional) probabilities of sequences for inhomogeneous models. |
class |
InhConstraint
This class is the superclass for all inhomogeneous constraints. |
class |
InhomogeneousDGM
This class is the main class for all inhomogeneous discrete graphical models ( InhomogeneousDGM ). |
class |
MEMConstraint
This constraint can be used for any maximum entropy model (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 (fixed
structure directed acyclic graphical
model). |
class |
IDGMParameterSet
This is the abstract container of parameters that is a 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 of the classifier together. |
class |
SharedStructureMixture
This class handles a mixture of models with the same structure that is 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
The 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 reverse complementary 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 |
AbstractBurnInTest
This abstract class implements some of the methods of BurnInTest to
alleviate the implementation of efficient and new burn-in tests. |
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 (see FSDAGModel ) that can be used in a Gibbs sampling. |
class |
FSDAGModelForGibbsSamplingParameterSet
The class for the parameters of a FSDAGModelForGibbsSampling . |
class |
SimpleBurnInTest
This is a very simple test for the length of the burn-in phase. |
class |
VarianceRatioBurnInTest
In this class the Variance-Ratio method of Gelman and Rubin is implemented to test the length of the burn-in phase of a multi-chain Gibbs Sampling (number of chains >2). |
Uses of Storable in de.jstacs.models.mixture.motif |
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Classes in de.jstacs.models.mixture.motif that implement Storable | |
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class |
HiddenMotifMixture
This is the main class that every generative motif discoverer should implement. |
class |
SingleHiddenMotifMixture
This class enables the user to search for a single motif in a sequence. |
Uses of Storable in de.jstacs.models.mixture.motif.positionprior |
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Classes in de.jstacs.models.mixture.motif.positionprior that implement Storable | |
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class |
GaussianLikePositionPrior
This class implements a gaussian like discrete truncated prior. |
class |
PositionPrior
This is the main class for any position prior that can be used in a motif discovery. |
class |
UniformPositionPrior
This prior implements a uniform distribution for the start position. |
Uses of Storable in de.jstacs.motifDiscovery |
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Subinterfaces of Storable in de.jstacs.motifDiscovery | |
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interface |
MotifDiscoverer
This is the interface that any tool for de-novo motif discovery should implement. |
interface |
MutableMotifDiscoverer
This is the interface that any tool for de-novo motif discovery should implement that allows any modify-operations like shift, shrink and expand. |
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
Container class for a set of Parameter s that can be used to
instantiate another class. |
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 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. |
class |
SequenceScoringParameterSet
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
and thus does nothing in the method SimpleParameterSet.loadParameters() . |
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 values. |
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 interface Constraint . |
class |
SimpleStaticConstraint
Class for a Constraint that checks values against static values using
the comparison operators defined in the interface Constraint . |
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 | |
---|---|
StorableValidator(Class<? extends Storable> clazz)
Creates a new StorableValidator for a subclass of
Storable . |
|
StorableValidator(Class<? extends Storable> clazz,
boolean trained)
Creates a new StorableValidator 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 String s. |
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 Result s 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
StorableResult . |
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 ScoringFunction s. |
interface |
ScoringFunction
This interface is the main part of any ScoreClassifier . |
interface |
VariableLengthScoringFunction
This is an interface for all NormalizableScoringFunction s that allow to score
subsequences of arbitrary length. |
Classes in de.jstacs.scoringFunctions that implement Storable | |
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class |
AbstractNormalizableScoringFunction
This class is the main part of any ScoreClassifier . |
class |
AbstractVariableLengthScoringFunction
This abstract class implements some methods declared in NormalizableScoringFunction based on the declaration
of methods in VariableLengthScoringFunction . |
class |
CMMScoringFunction
This scoring function implements a cyclic Markov model of arbitrary order and periodicity for any sequence length. |
class |
IndependentProductScoringFunction
This class enables the user to model parts of a sequence independent of each other. |
class |
MRFScoringFunction
This class implements the scoring function for any MRF (Markov Random Field). |
class |
NormalizedScoringFunction
This class makes an unnormalized ScoringFunction to a normalized ScoringFunction. |
class |
UniformScoringFunction
This ScoringFunction does nothing. |
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. |
class |
BayesianNetworkScoringFunctionParameterSet
Class for the parameters of a BayesianNetworkScoringFunction . |
class |
MutableMarkovModelScoringFunction
This class implements a AbstractNormalizableScoringFunction for an inhomogeneous Markov model. |
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. |
static class |
InhomogeneousMarkov.InhomogeneousMarkovParameterSet
Class for an InstanceParameterSet that defines the parameters of
an InhomogeneousMarkov structure Measure . |
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
. |
static class |
BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
Class for the parameters of a BTExplainingAwayResidual structure
Measure . |
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
. |
static class |
BTMutualInformation.BTMutualInformationParameterSet
Class for the parameters of a BTMutualInformation structure
Measure . |
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. |
static class |
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
Class for the parameters of a PMMExplainingAwayResidual structure
Measure . |
class |
PMMMutualInformation
Class for the network structure of a BayesianNetworkScoringFunction
that is a permuted Markov model based on mutual information. |
static class |
PMMMutualInformation.PMMMutualInformationParameterSet
Class for the parameters of a PMMMutualInformation structure
Measure . |
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 ScoringFunction s. |
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 scoring function (e.g. |
class |
MixtureScoringFunction
This class implements a real mixture model. |
class |
StrandScoringFunction
This class enables the user to search on both strand. |
class |
VariableLengthMixtureScoringFunction
This class implements a mixture of VariableLengthScoringFunction by extending MixtureScoringFunction and implementing the methods of VariableLengthScoringFunction . |
Uses of Storable in de.jstacs.scoringFunctions.mix.motifSearch |
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Classes in de.jstacs.scoringFunctions.mix.motifSearch that implement Storable | |
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class |
DurationScoringFunction
This class is the super class for all one dimensional position scoring functions that can be used as durations for semi Markov models. |
class |
HiddenMotifsMixture
This class handles mixtures with at least one hidden motif. |
class |
MixtureDuration
This class implements a mixture of DurationScoringFunction s. |
class |
PositionScoringFunction
This class implements a position scoring function that enables the user to get a score without using a Sequence object. |
class |
SkewNormalLikeScoringFunction
This class implements a skew normal like discrete truncated distribution. |
class |
UniformDurationScoringFunction
This scoring function implements a uniform distribution for positions. |
Uses of Storable in de.jstacs.utils |
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Classes in de.jstacs.utils that implement Storable | |
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class |
DoubleList
A simple list of primitive type double . |
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