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Packages that use NormalizableScoringFunction | |
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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.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.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 |
Uses of NormalizableScoringFunction in de.jstacs.classifier.scoringFunctionBased.logPrior |
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Fields in de.jstacs.classifier.scoringFunctionBased.logPrior declared as NormalizableScoringFunction | |
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protected NormalizableScoringFunction[] |
SeparateLogPrior.funs
The ScoringFunction s using the parameters that shall be
penalized. |
Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions |
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Classes in de.jstacs.scoringFunctions that implement NormalizableScoringFunction | |
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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 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. |
class |
VariableLengthScoringFunction
This is the main class for all ScoringFunction s that allow to score
subsequences of arbitrary length. |
Methods in de.jstacs.scoringFunctions that return NormalizableScoringFunction | |
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NormalizableScoringFunction |
NormalizedScoringFunction.getFunction()
This method returns the internal function. |
static NormalizableScoringFunction |
NormalizedScoringFunction.getNormalizedVersion(NormalizableScoringFunction nsf,
int starts)
This method returns a normalized version of a NormalizableScoringFunction. |
Methods in de.jstacs.scoringFunctions with parameters of type NormalizableScoringFunction | |
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static NormalizableScoringFunction |
NormalizedScoringFunction.getNormalizedVersion(NormalizableScoringFunction nsf,
int starts)
This method returns a normalized version of a NormalizableScoringFunction. |
static boolean |
AbstractNormalizableScoringFunction.isNormalized(NormalizableScoringFunction... function)
This method checks whether all given NormalizableScoringFunction s
are normalized. |
Constructors in de.jstacs.scoringFunctions with parameters of type NormalizableScoringFunction | |
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IndependentProductScoringFunction(NormalizableScoringFunction... functions)
This constructor creates an instance of an IndependentProductScoringFunction from a given series of
independent NormalizableScoringFunction s. |
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IndependentProductScoringFunction(NormalizableScoringFunction[] functions,
int[] length)
This constructor creates an instance of an IndependentProductScoringFunction from given series of
independent NormalizableScoringFunction s and lengths. |
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NormalizedScoringFunction(NormalizableScoringFunction nsf,
int starts)
Creates a new instance using a given NormalizableScoringFunction. |
Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions.directedGraphicalModels |
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Classes in de.jstacs.scoringFunctions.directedGraphicalModels that implement NormalizableScoringFunction | |
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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 |
MutableMarkovModelScoringFunction
This class implements a NormalizableScoringFunction for an inhomogeneous Markov model. |
Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions.homogeneous |
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Classes in de.jstacs.scoringFunctions.homogeneous that implement NormalizableScoringFunction | |
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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 NormalizableScoringFunction in de.jstacs.scoringFunctions.mix |
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Classes in de.jstacs.scoringFunctions.mix that implement NormalizableScoringFunction | |
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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. |
Fields in de.jstacs.scoringFunctions.mix declared as NormalizableScoringFunction | |
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protected NormalizableScoringFunction[] |
AbstractMixtureScoringFunction.function
This array contains the internal ScoringFunction s that are used to
determine the score. |
Methods in de.jstacs.scoringFunctions.mix that return NormalizableScoringFunction | |
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NormalizableScoringFunction |
AbstractMixtureScoringFunction.getFunction(int index)
This method returns a specific internal function. |
NormalizableScoringFunction[] |
AbstractMixtureScoringFunction.getFunctions()
This method returns an array of clones of the internal used functions. |
NormalizableScoringFunction[] |
AbstractMixtureScoringFunction.getScoringFunctions()
Returns a deep copy of all internal used ScoringFunction s. |
Methods in de.jstacs.scoringFunctions.mix with parameters of type NormalizableScoringFunction | |
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protected void |
AbstractMixtureScoringFunction.cloneFunctions(NormalizableScoringFunction[] originalFunctions)
This method clones the given array of functions and enables the user to do some post-processing. |
Constructors in de.jstacs.scoringFunctions.mix with parameters of type NormalizableScoringFunction | |
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AbstractMixtureScoringFunction(int length,
int starts,
int dimension,
boolean optimizeHidden,
boolean plugIn,
NormalizableScoringFunction... function)
This constructor creates a new AbstractMixtureScoringFunction . |
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MixtureScoringFunction(int starts,
boolean plugIn,
NormalizableScoringFunction... component)
This constructor creates a new MixtureScoringFunction . |
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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. |
Uses of NormalizableScoringFunction in de.jstacs.scoringFunctions.mix.motifSearch |
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Classes in de.jstacs.scoringFunctions.mix.motifSearch that implement NormalizableScoringFunction | |
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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 |
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. |
Constructors in de.jstacs.scoringFunctions.mix.motifSearch with parameters of type NormalizableScoringFunction | |
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HiddenMotifsMixture(boolean type,
int length,
int starts,
boolean plugIn,
HomogeneousScoringFunction bg,
NormalizableScoringFunction[] motif,
DurationScoringFunction[] posPrior,
boolean plugInBg)
This constructor creates an instance of HiddenMotifsMixture that allows to have one site of the specified motifs in a Sequence . |
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HiddenMotifsMixture(boolean type,
int length,
int starts,
boolean plugIn,
HomogeneousScoringFunction bg,
NormalizableScoringFunction[] motif,
DurationScoringFunction[] posPrior,
double sign,
boolean plugInBg)
This constructor creates an instance of HiddenMotifsMixture that allows to have one site of the specified motifs in a Sequence . |
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HiddenMotifsMixture(boolean type,
int length,
int starts,
boolean plugIn,
HomogeneousScoringFunction bg,
NormalizableScoringFunction motif,
DurationScoringFunction posPrior,
boolean plugInBg)
This constructor creates an instance of HiddenMotifsMixture that is either an OOPS or a ZOOPS model depending on the chosen type . |
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HiddenMotifsMixture(boolean type,
int length,
int starts,
boolean plugIn,
HomogeneousScoringFunction bg,
NormalizableScoringFunction motif,
DurationScoringFunction posPrior,
double sign,
boolean plugInBg)
This constructor creates an instance of HiddenMotifsMixture that is either an OOPS or a ZOOPS model depending on the chosen type . |
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