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Packages that use WrongAlphabetException | |
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de.jstacs.classifier.assessment | This package allows to assess classifiers. |
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.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.bioJava | Provides an adapter between the representation of data in BioJava and the representation used in Jstacs. |
de.jstacs.data.sequences | Provides classes for representing sequences. |
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.inhomogeneous | This package contains various inhomogeneous models. |
de.jstacs.models.discrete.inhomogeneous.shared | |
de.jstacs.models.mixture | This package is the super package for any mixture model. |
de.jstacs.models.mixture.motif | |
de.jstacs.scoringFunctions.mix | Provides ScoringFunction s that are mixtures of other ScoringFunction s. |
Uses of WrongAlphabetException in de.jstacs.classifier.assessment |
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Methods in de.jstacs.classifier.assessment that throw WrongAlphabetException | |
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ListResult |
ClassifierAssessment.assess(MeasureParameters mp,
ClassifierAssessmentAssessParameterSet assessPS,
ProgressUpdater pU,
Sample... s)
Assesses the contained classifiers. |
ListResult |
ClassifierAssessment.assess(MeasureParameters mp,
ClassifierAssessmentAssessParameterSet assessPS,
ProgressUpdater pU,
Sample[][]... s)
Assesses the contained classifiers. |
ListResult |
ClassifierAssessment.assess(MeasureParameters mp,
ClassifierAssessmentAssessParameterSet assessPS,
Sample... s)
Assesses the contained classifiers. |
protected void |
ClassifierAssessment.prepareAssessment(Sample... s)
Prepares an assessment. |
Constructors in de.jstacs.classifier.assessment that throw WrongAlphabetException | |
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ClassifierAssessment(AbstractClassifier... aCs)
Creates a new ClassifierAssessment from a set of
AbstractClassifier s. |
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ClassifierAssessment(AbstractClassifier[] aCs,
boolean buildClassifiersByCrossProduct,
Model[]... aMs)
This constructor allows to assess a collection of given AbstractClassifier s and, in addition, classifiers that will be
constructed using the given AbstractModel s. |
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ClassifierAssessment(AbstractClassifier[] aCs,
Model[][] aMs,
boolean buildClassifiersByCrossProduct,
boolean checkAlphabetConsistencyAndLength)
Creates a new ClassifierAssessment from an array of
AbstractClassifier s and a two-dimensional array of Model
s, which are combined to additional classifiers. |
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ClassifierAssessment(boolean buildClassifiersByCrossProduct,
Model[]... aMs)
Creates a new ClassifierAssessment from a set of Model s. |
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KFoldCrossValidation(AbstractClassifier... aCs)
Creates a new KFoldCrossValidation from a set of
AbstractClassifier s. |
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KFoldCrossValidation(AbstractClassifier[] aCs,
boolean buildClassifiersByCrossProduct,
Model[]... aMs)
This constructor allows to assess a collection of given AbstractClassifier s and those constructed using the given
AbstractModel s by a KFoldCrossValidation
. |
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KFoldCrossValidation(AbstractClassifier[] aCs,
Model[][] aMs,
boolean buildClassifiersByCrossProduct,
boolean checkAlphabetConsistencyAndLength)
Creates a new KFoldCrossValidation from an array of
AbstractClassifier s and a two-dimensional array of Model
s, which are combined to additional classifiers. |
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KFoldCrossValidation(boolean buildClassifiersByCrossProduct,
Model[]... aMs)
Creates a new KFoldCrossValidation from a set of Model s. |
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RepeatedHoldOutExperiment(AbstractClassifier... aCs)
Creates a new RepeatedHoldOutExperiment from a set of
AbstractClassifier s. |
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RepeatedHoldOutExperiment(AbstractClassifier[] aCs,
boolean buildClassifiersByCrossProduct,
Model[]... aMs)
This constructor allows to assess a collection of given AbstractClassifier s and those constructed using the given
AbstractModel s by a
RepeatedHoldOutExperiment . |
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RepeatedHoldOutExperiment(AbstractClassifier[] aCs,
Model[][] aMs,
boolean buildClassifiersByCrossProduct,
boolean checkAlphabetConsistencyAndLength)
Creates a new RepeatedHoldOutExperiment from an array of
AbstractClassifier s and a two-dimensional array of Model
s, which are combined to additional classifiers. |
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RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct,
Model[]... aMs)
Creates a new RepeatedHoldOutExperiment from a set of
Model s. |
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RepeatedSubSamplingExperiment(AbstractClassifier... aCs)
Creates a new RepeatedSubSamplingExperiment from a set of
AbstractClassifier s. |
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RepeatedSubSamplingExperiment(AbstractClassifier[] aCs,
boolean buildClassifiersByCrossProduct,
Model[]... aMs)
This constructor allows to assess a collection of given AbstractClassifier s and those constructed using the given
AbstractModel s by a
RepeatedSubSamplingExperiment . |
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RepeatedSubSamplingExperiment(AbstractClassifier[] aCs,
Model[][] aMs,
boolean buildClassifiersByCrossProduct,
boolean checkAlphabetConsistencyAndLength)
Creates a new RepeatedSubSamplingExperiment from an array of
AbstractClassifier s and a two-dimensional array of Model
s, which are combined to additional classifiers. |
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RepeatedSubSamplingExperiment(boolean buildClassifiersByCrossProduct,
Model[]... aMs)
Creates a new RepeatedSubSamplingExperiment from a set of
Model s. |
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Sampled_RepeatedHoldOutExperiment(AbstractClassifier... aCs)
Creates a new Sampled_RepeatedHoldOutExperiment from a set of
AbstractClassifier s. |
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Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs,
boolean buildClassifiersByCrossProduct,
Model[]... aMs)
This constructor allows to assess a collection of given AbstractClassifier s and those constructed using the given
AbstractModel s by a
Sampled_RepeatedHoldOutExperiment . |
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Sampled_RepeatedHoldOutExperiment(AbstractClassifier[] aCs,
Model[][] aMs,
boolean buildClassifiersByCrossProduct,
boolean checkAlphabetConsistencyAndLength)
Creates a new Sampled_RepeatedHoldOutExperiment from an array of
AbstractClassifier s and a two-dimensional array of Model
s, which are combined to additional classifiers. |
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Sampled_RepeatedHoldOutExperiment(boolean buildClassifiersByCrossProduct,
Model[]... aMs)
Creates a new Sampled_RepeatedHoldOutExperiment from a set of
Model s. |
Uses of WrongAlphabetException in de.jstacs.classifier.scoringFunctionBased |
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Constructors in de.jstacs.classifier.scoringFunctionBased that throw WrongAlphabetException | |
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AbstractOptimizableFunction(Sample[] data,
double[][] weights,
boolean norm,
boolean freeParams)
The constructor creates an instance using the given weighted data. |
Uses of WrongAlphabetException in de.jstacs.classifier.scoringFunctionBased.cll |
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Constructors in de.jstacs.classifier.scoringFunctionBased.cll that throw WrongAlphabetException | |
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NormConditionalLogLikelihood(ScoringFunction[] score,
Sample[] data,
double[][] weights,
boolean norm,
boolean freeParams)
The constructor creates an instance of the NormConditionalLogLikelihood . |
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NormConditionalLogLikelihood(ScoringFunction[] score,
Sample[] data,
double[][] weights,
LogPrior prior,
boolean norm,
boolean freeParams)
The constructor creates an instance of the NormConditionalLogLikelihood using the given prior. |
Uses of WrongAlphabetException in de.jstacs.data |
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Methods in de.jstacs.data that throw WrongAlphabetException | |
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static Sequence |
Sequence.create(AlphabetContainer con,
SequenceAnnotation[] annotation,
String sequence,
String delim)
Creates a Sequence.CompositeSequence from a String based on the given
AlphabetContainer using the given delimiter delim
and some annotation for the Sequence.CompositeSequence . |
static Sequence |
Sequence.create(AlphabetContainer con,
String sequence)
Creates a Sequence.CompositeSequence from a String based on the given
AlphabetContainer using the standard delimiter for this
AlphabetContainer . |
static Sequence |
Sequence.create(AlphabetContainer con,
String sequence,
String delim)
Creates a Sequence.CompositeSequence from a String based on the given
AlphabetContainer using the given delimiter delim . |
double |
AlphabetContainer.getCode(int pos,
String sym)
Returns the encoded symbol for sym of the Alphabet
of position pos of this AlphabetContainer . |
Uses of WrongAlphabetException in de.jstacs.data.alphabets |
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Methods in de.jstacs.data.alphabets that throw WrongAlphabetException | |
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int |
DiscreteAlphabet.getCode(String symbol)
Returns the code of a given symbol. |
Uses of WrongAlphabetException in de.jstacs.data.bioJava |
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Methods in de.jstacs.data.bioJava that throw WrongAlphabetException | |
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static SequenceIterator |
BioJavaAdapter.sampleToSequenceIterator(Sample sample,
boolean flat)
Creates a SequenceIterator from the Sample
sample preserving as much annotation as possible. |
Uses of WrongAlphabetException in de.jstacs.data.sequences |
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Constructors in de.jstacs.data.sequences that throw WrongAlphabetException | |
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ArbitrarySequence(AlphabetContainer alphabetContainer,
double[] content)
Creates a new ArbitrarySequence from an array of
double -encoded alphabet symbols. |
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ArbitrarySequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
String sequence,
String delim)
Creates a new ArbitrarySequence from a String
representation using the delimiter delim . |
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ArbitrarySequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
SymbolExtractor extractor)
Creates a new ArbitrarySequence from a SymbolExtractor . |
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ArbitrarySequence(AlphabetContainer alphabetContainer,
String sequence)
Creates a new ArbitrarySequence from a String
representation using the default delimiter. |
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ByteSequence(AlphabetContainer alphabetContainer,
byte[] content)
Creates a new ByteSequence from an array of byte -
encoded alphabet symbols. |
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ByteSequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
String sequence,
String delim)
Creates a new ByteSequence from a String representation
using the delimiter delim . |
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ByteSequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
SymbolExtractor extractor)
Creates a new ByteSequence from a SymbolExtractor . |
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ByteSequence(AlphabetContainer alphabetContainer,
String sequence)
Creates a new ByteSequence from a String representation
using the default delimiter. |
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DiscreteSequence(AlphabetContainer container,
SequenceAnnotation[] annotation)
This constructor creates a new DiscreteSequence with the
AlphabetContainer container and the annotation
annotation but without the content. |
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IntSequence(AlphabetContainer alphabetContainer,
int... content)
Creates a new IntSequence from an array of int -
encoded alphabet symbols. |
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IntSequence(AlphabetContainer alphabetContainer,
int[] content,
int start,
int length)
Creates a new IntSequence from a part of the array of
int - encoded alphabet symbols. |
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IntSequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
String sequence,
String delim)
Creates a new IntSequence from a String representation
using the delimiter delim . |
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IntSequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
SymbolExtractor extractor)
Creates a new IntSequence from a SymbolExtractor . |
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IntSequence(AlphabetContainer alphabetContainer,
String sequence)
Creates a new IntSequence from a String representation
using the default delimiter. |
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PermutedSequence(Sequence seq)
Creates a new PermutedSequence by shuffling the symbols of a
given Sequence . |
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ShortSequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
String sequence,
String delim)
Creates a new ShortSequence from a String representation
using the delimiter delim . |
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ShortSequence(AlphabetContainer alphabetContainer,
SequenceAnnotation[] annotation,
SymbolExtractor extractor)
Creates a new ShortSequence from a SymbolExtractor . |
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ShortSequence(AlphabetContainer alphabetContainer,
short[] content)
Creates a new ShortSequence from an array of short -
encoded alphabet symbols. |
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ShortSequence(AlphabetContainer alphabetContainer,
String sequence)
Creates a new ShortSequence from a String representation
using the default delimiter. |
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SparseSequence(AlphabetContainer alphCon,
String seq)
Creates a new SparseSequence from a String
representation. |
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SparseSequence(AlphabetContainer alphCon,
SymbolExtractor se)
Creates a new SparseSequence from a SymbolExtractor . |
Uses of WrongAlphabetException in de.jstacs.models |
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Methods in de.jstacs.models that throw WrongAlphabetException | |
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double |
UniformModel.getProbFor(Sequence sequence,
int startpos,
int endpos)
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Constructors in de.jstacs.models that throw WrongAlphabetException | |
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CompositeModel(AlphabetContainer alphabets,
int[] assignment,
Model... models)
Creates a new CompositeModel . |
Uses of WrongAlphabetException in de.jstacs.models.discrete |
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Methods in de.jstacs.models.discrete that throw WrongAlphabetException | |
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static double |
ConstraintManager.countInhomogeneous(AlphabetContainer alphabets,
int length,
Sample data,
double[] weights,
boolean reset,
Constraint... constr)
Fills the (inhomogeneous) Constraint constr with the
weighted absolute frequencies of the Sample data . |
Uses of WrongAlphabetException in de.jstacs.models.discrete.homogeneous |
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Methods in de.jstacs.models.discrete.homogeneous that throw WrongAlphabetException | |
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Sample |
HomogeneousModel.emitSample(int no,
int... length)
Creates a Sample of a given number of Sequence s from a
trained homogeneous model. |
protected abstract Sequence |
HomogeneousModel.getRandomSequence(Random r,
int length)
This method creates a random Sequence from a trained homogeneous
model. |
protected Sequence |
HomogeneousMM.getRandomSequence(Random r,
int length)
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Uses of WrongAlphabetException in de.jstacs.models.discrete.inhomogeneous |
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Methods in de.jstacs.models.discrete.inhomogeneous that throw WrongAlphabetException | |
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SymmetricTensor |
StructureLearner.getTensor(Sample data,
double[] weights,
byte order,
StructureLearner.LearningType method)
This method can be used to compute a Tensor that can be used to
determine the optimal structure. |
Uses of WrongAlphabetException in de.jstacs.models.discrete.inhomogeneous.shared |
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Constructors in de.jstacs.models.discrete.inhomogeneous.shared that throw WrongAlphabetException | |
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SharedStructureMixture(FSDAGModel[] m,
StructureLearner.ModelType model,
byte order,
int starts,
boolean estimateComponentProbs,
double[] weights,
double alpha,
double epsilon)
Creates a new SharedStructureMixture instance with all relevant
values. |
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SharedStructureMixture(FSDAGModel[] m,
StructureLearner.ModelType model,
byte order,
int starts,
double[] weights,
double alpha,
double epsilon)
Creates a new SharedStructureMixture instance with fixed
component weights. |
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SharedStructureMixture(FSDAGModel[] m,
StructureLearner.ModelType model,
byte order,
int starts,
double alpha,
double epsilon)
Creates a new SharedStructureMixture instance which estimates the
component probabilities/weights. |
Uses of WrongAlphabetException in de.jstacs.models.mixture |
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Constructors in de.jstacs.models.mixture that throw WrongAlphabetException | |
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AbstractMixtureModel(int length,
Model[] models,
boolean[] optimizeModel,
int dimension,
int starts,
boolean estimateComponentProbs,
double[] componentHyperParams,
double[] weights,
AbstractMixtureModel.Algorithm algorithm,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates a new AbstractMixtureModel . |
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MixtureModel(int length,
Model[] models,
double[] weights,
int starts,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization)
Creates an instance using EM and fixed component probabilities. |
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MixtureModel(int length,
Model[] models,
double[] weights,
int starts,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates an instance using Gibbs Sampling and fixed component probabilities. |
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MixtureModel(int length,
Model[] models,
int starts,
boolean estimateComponentProbs,
double[] componentHyperParams,
double[] weights,
AbstractMixtureModel.Algorithm algorithm,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates a new MixtureModel . |
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MixtureModel(int length,
Model[] models,
int starts,
double[] componentHyperParams,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization)
Creates an instance using EM and estimating the component probabilities. |
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MixtureModel(int length,
Model[] models,
int starts,
double[] componentHyperParams,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates an instance using Gibbs Sampling and sampling the component probabilities. |
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StrandModel(Model model,
int starts,
boolean estimateComponentProbs,
double[] componentHyperParams,
double forwardStrandProb,
AbstractMixtureModel.Algorithm algorithm,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates a new StrandModel . |
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StrandModel(Model model,
int starts,
double[] componentHyperParams,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization)
Creates an instance using EM and estimating the component probabilities. |
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StrandModel(Model model,
int starts,
double[] componentHyperParams,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates an instance using Gibbs Sampling and sampling the component probabilities. |
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StrandModel(Model model,
int starts,
double forwardStrandProb,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization)
Creates an instance using EM and fixed component probabilities. |
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StrandModel(Model model,
int starts,
double forwardStrandProb,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates an instance using Gibbs Sampling and fixed component probabilities. |
Uses of WrongAlphabetException in de.jstacs.models.mixture.motif |
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Constructors in de.jstacs.models.mixture.motif that throw WrongAlphabetException | |
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HiddenMotifMixture(Model[] models,
boolean[] optimzeArray,
int components,
int starts,
boolean estimateComponentProbs,
double[] componentHyperParams,
double[] weights,
PositionPrior posPrior,
AbstractMixtureModel.Algorithm algorithm,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates a new HiddenMotifMixture . |
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SingleHiddenMotifMixture(Model motif,
Model bg,
boolean trainOnlyMotifModel,
int starts,
double[] componentHyperParams,
double[] weights,
PositionPrior posPrior,
AbstractMixtureModel.Algorithm algorithm,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization,
int initialIteration,
int stationaryIteration,
BurnInTest burnInTest)
Creates a new SingleHiddenMotifMixture . |
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SingleHiddenMotifMixture(Model motif,
Model bg,
boolean trainOnlyMotifModel,
int starts,
double[] componentHyperParams,
PositionPrior posPrior,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization)
Creates a new SingleHiddenMotifMixture using EM and estimating
the probability for finding a motif. |
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SingleHiddenMotifMixture(Model motif,
Model bg,
boolean trainOnlyMotifModel,
int starts,
double motifProb,
PositionPrior posPrior,
double alpha,
double eps,
AbstractMixtureModel.Parameterization parametrization)
Creates a new SingleHiddenMotifMixture using EM and fixed
probability for finding a motif. |
Uses of WrongAlphabetException in de.jstacs.scoringFunctions.mix |
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Constructors in de.jstacs.scoringFunctions.mix that throw WrongAlphabetException | |
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StrandScoringFunction(NormalizableScoringFunction function,
double forwardPartOfESS,
int starts,
boolean plugIn,
StrandScoringFunction.InitMethod initMethod)
This constructor creates a StrandScoringFunction that optimizes the usage of each strand. |
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StrandScoringFunction(NormalizableScoringFunction function,
int starts,
boolean plugIn,
StrandScoringFunction.InitMethod initMethod,
double forward)
This constructor creates a StrandScoringFunction that has a fixed frequency for the strand usage. |
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