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Parameter
and generates the internal id.
BayesianNetworkScoringFunction
.index
in the list of parameters of the BayesianNetworkScoringFunction
and responsible for symbol
at position position
and pseudo count pseudoCount
.
index
in the list of parameters of the BayesianNetworkScoringFunction
and responsible for symbol
at position position
having context context
and pseudo count pseudoCount
.
Parameter.toXML()
} method.
ParameterException
with the specified error message.
ParameterException
without specific message
Parameter
that can be removed from the set.
ParameterSet
describing this DiscreteAlphabet
ParameterSet
that holds the possible values
Parameter
s.ParameterSet
from the class that can be instantiated using
this ParameterSet
.
ParameterSet
with empty parameter values.
ParameterSet
out of an array of parameters.
ParameterSet
out of an ArrayList
of parameters.
ParameterSet
out of an XML representation
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.
Parameter
that contains a ParameterSet
as value.ParameterSetContainer
out of a ParameterSet
.
ParameterSetContainer
from its XML-representation.
Parameter
s und creates instances of InstantiableFromParameterSet
s
from a ParameterSet
.Exception
that is thrown if an instance of some class could not be created.NotInstantiableException
from an error-message.
that is thrown if the datatype of a Parameter
is not appropriate for some purpose.- ParameterSetParser.WrongParameterTypeException(String) -
Constructor for exception de.jstacs.io.ParameterSetParser.WrongParameterTypeException
- Creates a new instance of a
WrongParameterTypeException
from an error-message
- parametersLoaded() -
Method in class de.jstacs.parameters.ParameterSet
- Returns
true
if the parameters of this
ParameterSet
have already been loaded using the
loadParameters()
-method
- ParameterTree - Class in de.jstacs.scoringFunctions.directedGraphicalModels
- Class for the tree that represents the context of a
Parameter
in a BayesianNetworkScoringFunction
. - ParameterTree(int, int[], AlphabetContainer, int, int[]) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
- Creates a new
ParameterTree
for the parameters at position pos
using the parent positions in contextPoss
.
- ParameterTree(StringBuffer, AlphabetContainer) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
- Re-creates a
ParameterTree
from its XML-representation as returned by ParameterTree.toXML()
.
- ParameterValidator - Interface in de.jstacs.parameters.validation
- Interface for a parameter validator, i.e. a class that can validate some possible parameter value.
- paramRef -
Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
- This array contains the references/indices for the parameters.
- params -
Variable in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
- The parameter set for the classifier.
- params -
Variable in class de.jstacs.models.discrete.DiscreteGraphicalModel
- The current parameter set of the model
- paramsFile -
Variable in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
- The files for saving the parameters while the sampling.
- parent -
Variable in class de.jstacs.parameters.Parameter
- If this
Parameter
is enclosed in a ParameterSet
,
this variable holds a reference to that ParameterSet
.
- parent -
Variable in class de.jstacs.parameters.ParameterSet
- Is this
ParameterSet
is contained in a ParameterSetContainer
,
this variable holds a reference to that ParameterSetContainer
.
- parseNextParameterSet() -
Method in class de.jstacs.models.mixture.AbstractMixtureModel
- This method allows the user to parse the next set of parameters (from a file).
- parseNextParameterSet() -
Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
-
- parseNextParameterSet() -
Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
- This method allows the user to parse the next set of parameters (from a file).
- parseParameterSet(int, int) -
Method in class de.jstacs.models.mixture.AbstractMixtureModel
- This method allows the user to parse the set of parameters with index
burnInIteration
of a specific
sampling
(from a file).
- parseParameterSet(int, int) -
Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
-
- parseParameterSet(int, int) -
Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
- This method allows the user to parse the set of parameters with index
n
of a certain
sampling
(from a file).
- parseSections(String) -
Static method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
- Parsed the sections as defined in
sections
to a list of Integer
s.
- partition(double, Sample.PartitionMethod, int) -
Method in class de.jstacs.data.Sample
- This method partitions the elements of the sample in
2
distinct parts.
- partition(Sample.PartitionMethod, double...) -
Method in class de.jstacs.data.Sample
- This method partitions the elements of the sample in distinct parts.
- partition(int, Sample.PartitionMethod) -
Method in class de.jstacs.data.Sample
- This method partitions the elements of the sample in
k
distinct parts.
- partNorm -
Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
- This array contains the partial normalization constants, i.e. the normalization constant for each component.
- PermutedSequence - Class in de.jstacs.data.sequences
- Class for a permuted sequence.
- PermutedSequence(Sequence) -
Constructor for class de.jstacs.data.sequences.PermutedSequence
- This constructor creates an instance by shuffling the symbols.
- plot(REnvironment, AbstractScoreBasedClassifier.DoubleTableResult...) -
Static method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult
- This method plots an array of
DoubleTableResult
in one image
- plot(String) -
Method in class de.jstacs.utils.REnvironment
- Creates a buffered image form a given plot command.
- plot(String, double, double) -
Method in class de.jstacs.utils.REnvironment
- Creates a buffered image with given dimension form a given plot command.
- plotScores(AbstractScoreBasedClassifier, Sample, Sample, REnvironment, int, double, String) -
Static method in class de.jstacs.classifier.utils.ClassificationVisualizer
- This method returns an ImageResult containing a plot of the histograms of the scores.
- plotScores(AbstractScoreBasedClassifier, Sample, Sample, REnvironment, int, double, String, String) -
Static method in class de.jstacs.classifier.utils.ClassificationVisualizer
- This method creates a pdf containing a plot of the histograms of the scores.
- plotToPDF(String, String, boolean) -
Method in class de.jstacs.utils.REnvironment
- Creates a pdf file form a given plot command.
- plotToPDF(String, double, double, String, boolean) -
Method in class de.jstacs.utils.REnvironment
- Creates a pdf file with given dimension form a given plot command.
- plotToTexFile(String, String, boolean) -
Method in class de.jstacs.utils.REnvironment
- Creates a tex file form a given plot command.
- plotToTexFile(String, double, double, String, boolean) -
Method in class de.jstacs.utils.REnvironment
- Creates a tex file with given dimension form a given plot command.
- plugIn -
Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
- This boolean indicates whether to use a plug-in strategy to initialize the instance.
- plugInParameters -
Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
- Indicates if plug-in parameters, i.e. generative (MAP) parameters shall be used upon initialization
- PMMExplainingAwayResidual - 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 the explaining away residual. - PMMExplainingAwayResidual(StringBuffer) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
- Re-creates a
PMMExplainingAwayResidual
from its XML-representation as returned by PMMExplainingAwayResidual.toXML()
.
- PMMExplainingAwayResidual(byte, double[]) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
- Creates a new
PMMExplainingAwayResidual
of order order
.
- 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, int, double[]) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- Creates a new
PMMMutualInformation
of order order
.
- PMMMutualInformation(StringBuffer) -
Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- Re-creates a
PMMMutualInformation
from its XML-representation as returned by PMMMutualInformation.toXML()
.
- position -
Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
- The position of
symbol
this parameter is responsible for.
- powers -
Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
-
- precomputeNorm() -
Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
- Precomutes the normalisation constant.
- precomputeNormalization() -
Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
- Precomputes all normalization constants and saves the global normalization constant to
BayesianNetworkScoringFunction.normalizationConstant
.
- prepareAssessment(Sample...) -
Method in class de.jstacs.classifier.assessment.ClassifierAssessment
- Prepares an assessment.
- 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.cll.CLLClassifier
- The prior that is used in this instance.
- 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.
- pseudoCount -
Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
- The pseudo count 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
-
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