|
||||||||||
PREV LETTER NEXT LETTER | FRAMES NO FRAMES |
element1
and element2
.
String
s.String
s and the
edit-costs.
[lower,upper]
.
[lower,upper]
.
Parameter
and generates the internal id.
BayesianNetworkScoringFunction
.Parameter
, that is Parameter
no
index
in the list of Parameter
s of the
BayesianNetworkScoringFunction
and responsible for
symbol
at position position
and pseudo count
pseudoCount
.
Parameter
, that is Parameter
no
index
in the list of Parameter
s of the
BayesianNetworkScoringFunction
and responsible for
symbol
at position position
having context
context
and pseudocount pseudoCount
.
Storable
.
ParameterException
with the specified error
message.
ParameterException
without a specific message.
true
if there is still a Parameter
that can
be removed from the set.
DiscreteAlphabet
.
ParameterSet
that holds the possible values
Parameter
s.ParameterSet
with empty parameter values.
ParameterSet
out of an array of Parameter
s.
ParameterSet
out of an ArrayList
of
Parameter
s.
Storable
.
List
of Parameter
s that basically
has the same functionality as ArrayList
, but additionally takes
care of the references Parameter.parent
.ParameterSet.ParameterList
.
ParameterSet.ParameterList
from an existing
Collection
of Parameter
s.
ParameterSet.ParameterList
with a defined initial
capacity.
ParameterSetContainer
that contains a
ParameterSet
as value.ParameterSetContainer
out of a
ParameterSet
.
Storable
.
Parameter
s and creates instances of
InstantiableFromParameterSet
s from a ParameterSet
.Exception
that is thrown if an instance of some class could
not be created.ParameterSetParser.NotInstantiableException
with a
given error message.
Exception
that is thrown if the DataType
of a
Parameter
is not appropriate for some purpose.ParameterSetParser.WrongParameterTypeException
with
a given error message.
Parameter
of ParameterSet
.ParameterSet
s.
Map.Entry
that sorts by the key of the Map.Entry
.Comparator
that only compares the keys of Map.Entry
s.
Map.Entry
where value is a ComparableElement
with weight Integer
.Comparator
that only compares the ranks of Map.Entry
s where the rank is determined by the ParameterSet.parameters
.
true
if the parameters of this ParameterSet
have already been loaded using ParameterSet.loadParameters()
.
Parameter
in a
BayesianNetworkScoringFunction
.ParameterTree
for the parameters at position
pos
using the parent positions in contextPoss
.
ParameterTree
from its XML representation as
returned by ParameterTree.toXML()
.
ParameterTree
Storable
interface.
Parameter
is enclosed in a ParameterSet
, this
variable holds a reference to that ParameterSet
.
ParameterSet
is contained in a
ParameterSetContainer
, this variable holds a reference to that
ParameterSetContainer
.
String
representation of the given
SequenceAnnotation
s that can be used as comment line in a file.
HashSet
in a Hashtable
with unique indices starting at 0.
idx
of a certain sampling
(from a file).
burnInIteration
of a specific sampling
(from a
file).
n
of a certain sampling
(from a file).
sections
to a
LinkedList
of Integer
s.
original
String
to null
if original
equals "null".
Sequence
s, of the
Sample
in two distinct parts.
Sequence
s, of the
Sample
in distinct parts where each part holds the corresponding
percentage given in the array percentage
.
Sequence
s, of the
Sample
and the corresponding weights in distinct parts where each part holds the corresponding
percentage given in the array percentage
.
Sequence
s, of the
Sample
in k
distinct parts.
Sequence
s, of the
Sample
and the corresponding weights in k
distinct parts.
PermutedSequence
by shuffling the symbols of a
given Sequence
.
PermutedSequence
for a given permutation
PhyloDiscreteEmission
based on the equivalent sample size.
DiscreteEmission
defining the individual hyper parameters.
PhyloTree
A PhyloNode contains some basic informations of itself and the incoming edge
Furthermore it contains a list of PhyloNode
s that represent the children nodesStorable
.
Storable
.
AbstractScoreBasedClassifier.DoubleTableResult
s in one
image.
threshold
.
ImageResult
containing a plot of the
histograms of the scores.
mean
and standard deviation sd
.
PluginGaussianEmission
from its XML representation.
BayesianNetworkScoringFunction
that is a permuted Markov model based on the explaining away residual.Storable
.
PMMExplainingAwayResidual
of order
order
.
PMMExplainingAwayResidual
from the corresponding
InstanceParameterSet
parameters/code>.
- PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
- Class for the parameters of a
PMMExplainingAwayResidual
structure
Measure
. - PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet() -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
- Creates a new
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
with
empty parameter values.
- PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet(byte, double[]) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
- Creates a new
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
with the
parameter for the order set to order
and the parameter
for the equivalent sample sizes (ess) set to ess
.
- PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet(StringBuffer) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
- Creates a new
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
from its
XML representation as defined by the Storable
interface.
- PMMMutualInformation - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
- Class for the network structure of a
BayesianNetworkScoringFunction
that is a permuted Markov model based on mutual information. - PMMMutualInformation(byte, BTMutualInformation.DataSource, double[]) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- Creates a new
PMMMutualInformation
of order order
.
- PMMMutualInformation(PMMMutualInformation.PMMMutualInformationParameterSet) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- Creates a new
PMMMutualInformation
from the corresponding
InstanceParameterSet
parameters
.
- PMMMutualInformation(StringBuffer) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- The standard constructor for the interface
Storable
.
- PMMMutualInformation.PMMMutualInformationParameterSet - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
- Class for the parameters of a
PMMMutualInformation
structure
Measure
. - PMMMutualInformation.PMMMutualInformationParameterSet() -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
- Creates a new
PMMMutualInformation.PMMMutualInformationParameterSet
with empty
parameter values.
- PMMMutualInformation.PMMMutualInformationParameterSet(byte, BTMutualInformation.DataSource, double[]) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
- Creates a new
PMMMutualInformation.PMMMutualInformationParameterSet
with the
parameter for the order set to order
, the parameter for
the BTMutualInformation.DataSource
set to clazz
and the parameter
for the equivalent sample sizes (ess) set to ess
.
- PMMMutualInformation.PMMMutualInformationParameterSet(StringBuffer) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
- Creates a new
PMMMutualInformation.PMMMutualInformationParameterSet
from its
XML representation as defined by the Storable
interface.
- position -
Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
- The position of
symbol
this parameter is responsible for.
- PositionPrior - Class in de.jstacs.models.mixture.motif.positionprior
- This is the main class for any position prior that can be used in a motif
discovery.
- PositionPrior() -
Constructor for class de.jstacs.models.mixture.motif.positionprior.PositionPrior
- This empty constructor creates an instance with motif length -1.
- PositionPrior(StringBuffer) -
Constructor for class de.jstacs.models.mixture.motif.positionprior.PositionPrior
- The standard constructor for the interface
Storable
.
- PositionScoringFunction - Class in de.jstacs.scoringFunctions.mix.motifSearch
- This class implements a position scoring function that enables the user to get a score without using a Sequence
object.
- PositionScoringFunction(AlphabetContainer, int) -
Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction
- This constructor allows create instance with more than one dimension.
- PositionScoringFunction(int, int) -
Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction
- This is the main constructor that creates the
AlphabetContainer
internally.
- PositionScoringFunction(StringBuffer) -
Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction
- This is the constructor for
Storable
.
- posPrior -
Variable in class de.jstacs.models.mixture.motif.HiddenMotifMixture
- The prior for the positions.
- powers -
Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
- An array containing the powers for the number of nodes.
- powers -
Variable in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
- The powers of the alphabet length.
- precompute() -
Method in class de.jstacs.models.hmm.states.emissions.continuous.GaussianEmission
- This method precomputes some normalization constant.
- precompute() -
Method in class de.jstacs.models.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
- This method precomputes some normalization constant and probabilities.
- precompute() -
Method in class de.jstacs.models.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
- This method precomputes internal fields as for instance the normalization constant.
- precompute() -
Method in class de.jstacs.models.hmm.transitions.elements.ReferenceBasedTransitionElement
-
- precompute() -
Method in class de.jstacs.models.hmm.transitions.elements.TransitionElement
-
- precomputeBurnInLength(SamplingScoreBasedClassifier.ScoringFunctionSamplingComponent) -
Method in class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifier
- Precomputes the length of the burn-in phase, e.g. useful for computing scores of
multiple sequences
- precomputeNorm() -
Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
- Pre-computes the normalization constant.
- precomputeNormalization() -
Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
- Pre-computes all normalization constants.
- preoptimize(OptimizableFunction) -
Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
- This method allows to pre-optimize the parameter before the real optimization.
- prepareAssessment(Sample...) -
Method in class de.jstacs.classifier.assessment.ClassifierAssessment
- Prepares an assessment.
- previousParameters -
Variable in class de.jstacs.classifier.scoringFunctionBased.sampling.SamplingScoreBasedClassifier
- The previously accepted parameters, backup for rollbacks
- prGrad -
Variable in class de.jstacs.classifier.scoringFunctionBased.gendismix.LogGenDisMixFunction
- Array for the gradient of the prior
- print(PrintWriter) -
Method in class de.jstacs.results.ListResult
- Prints the information of this
ListResult
to the provided
PrintWriter
.
- print() -
Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
- Prints the counts and the value of this parameter to
System.out
.
- print() -
Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
- Prints the structure of this tree.
- prior -
Variable in class de.jstacs.classifier.scoringFunctionBased.gendismix.GenDisMixClassifier
- The prior that is used in this classifier.
- prior -
Variable in class de.jstacs.classifier.scoringFunctionBased.SFBasedOptimizableFunction
- The prior that is used in this function.
- PRIOR_INDEX -
Static variable in enum de.jstacs.classifier.scoringFunctionBased.gendismix.LearningPrinciple
- This constant is the array index of the weighting factor for the prior.
- probabilities -
Variable in class de.jstacs.models.hmm.transitions.elements.ReferenceBasedTransitionElement
- Represents the initial the transition probabilities.
- probFor(Sequence, int, int) -
Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM
-
- probFor(Sequence, int, int) -
Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
- This method computes the probability of the given
Sequence
in the
given interval.
- probs -
Variable in class de.jstacs.models.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
- The parameters transformed to probabilites
- probs -
Variable in class de.jstacs.models.hmm.transitions.elements.TransitionElement
- The precomputed probabilities for each possible transition.
- ProgressUpdater - Interface in de.jstacs.utils
- Interface for supervising the progress of long time processes like cross
validation.
- propagateId() -
Method in class de.jstacs.parameters.ParameterSet
- Propagates the id of this
ParameterSet
to all Parameter
s
above and below in the hierarchy.
- provideMatrix(int, int) -
Method in class de.jstacs.models.hmm.AbstractHMM
- This method invokes the method
AbstractHMM.createHelperVariables()
and provides the matrix with given type.
- pseudoCount -
Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
- The pseudocount for this parameter.
- PValueComputation - Class in de.jstacs.classifier.utils
- This class can be used to compute any p-value from a given statistic.
- PValueComputation() -
Constructor for class de.jstacs.classifier.utils.PValueComputation
-
|
||||||||||
PREV LETTER NEXT LETTER | FRAMES NO FRAMES |