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element1
and element2
.
String
s.String
s and the
edit-costs.
[lower,upper]
.
[lower,upper]
.
Parameter
.
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
.
AnnotatedEntityList
that automatically sets
the Parameter.parent
field to the enclosing ParameterSet
.ParameterSetContainer
that contains a
ParameterSet
as value.ParameterSetContainer
out of a ParameterSet
.
ParameterSetContainer
out of a
ParameterSet
.
ParameterSetContainer
out of the class
of a ParameterSet
.
ParameterSetContainer
out of the class
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 been loaded.
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.
n
of a certain sampling
(from a file).
idx
of a certain sampling
(from a file).
burnInIteration
of a specific sampling
(from a
file).
sections
to a
LinkedList
of Integer
s.
original
String
to null
if original
equals "null".
percent
percentile of the array, i.e.,
returns the element at percent*(array.length)
of the sorted array.
percent
percentile of the array between start and end, i.e.,
returns the element at percent*(end-start)
of the sorted sub-array.
AbstractClassifier
.AbstractPerformanceMeasure
s that can be used
in AbstractClassifier.evaluate(AbstractPerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...)
.Storable
.
PerformanceMeasureParameterSet
that can be used for classifiers that
handle the given number of classes.
PerformanceMeasureParameterSet
with the given performance measures.
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
.
ps
.
ps
.
ps
.
ps
.
ps
.
ps
.
ImageResult
containing a plot of the
histograms of the scores.
ps
.
ps
.
ps
.
mean
and standard deviation sd
.
PluginGaussianEmission
from its XML representation.
BayesianNetworkDiffSM
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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
- Class for the parameters of a
PMMExplainingAwayResidual
structure
Measure
. - PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet() -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
- Creates a new
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
with
empty parameter values.
- PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet(byte, double[]) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
- Class for the network structure of a
BayesianNetworkDiffSM
that is a permuted Markov model based on mutual information. - PMMMutualInformation(byte, BTMutualInformation.DataSource, double[]) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- Creates a new
PMMMutualInformation
of order order
.
- PMMMutualInformation(PMMMutualInformation.PMMMutualInformationParameterSet) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- Creates a new
PMMMutualInformation
from the corresponding
InstanceParameterSet
parameters
.
- PMMMutualInformation(StringBuffer) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
- The standard constructor for the interface
Storable
.
- PMMMutualInformation.PMMMutualInformationParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
- Class for the parameters of a
PMMMutualInformation
structure
Measure
. - PMMMutualInformation.PMMMutualInformationParameterSet() -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
- Creates a new
PMMMutualInformation.PMMMutualInformationParameterSet
from its
XML representation as defined by the Storable
interface.
- pop() -
Method in class de.jstacs.utils.IntList
- Returns the last element and removes it from the list.
- position -
Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
- The position of
symbol
this parameter is responsible for.
- PositionDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
- This class implements a position scoring function that enables the user to get a score without using a Sequence
object.
- PositionDiffSM(AlphabetContainer, int) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
- This constructor allows create instance with more than one dimension.
- PositionDiffSM(int, int) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
- This is the main constructor that creates the
AlphabetContainer
internally.
- PositionDiffSM(StringBuffer) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
- This is the constructor for
Storable
.
- PositionPrior - Class in de.jstacs.sequenceScores.statisticalModels.trainable.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.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
- This empty constructor creates an instance with motif length -1.
- PositionPrior(StringBuffer) -
Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
- The standard constructor for the interface
Storable
.
- PositivePredictiveValueForFixedSensitivity - Class in de.jstacs.classifiers.performanceMeasures
- This class implements the positive predictive value for a fixed sensitivity.
- PositivePredictiveValueForFixedSensitivity() -
Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
- Constructs a new instance of the performance measure
PositivePredictiveValueForFixedSensitivity
with empty parameter values.
- PositivePredictiveValueForFixedSensitivity(double) -
Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
- Constructs a new instance of the performance measure
PositivePredictiveValueForFixedSensitivity
with given sensitivity
.
- PositivePredictiveValueForFixedSensitivity(StringBuffer) -
Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
- The standard constructor for the interface
Storable
.
- posPrior -
Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.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.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
- The powers of the alphabet length.
- PRCurve - Class in de.jstacs.classifiers.performanceMeasures
- This class implements the precision-recall curve and its area under the curve.
- PRCurve() -
Constructor for class de.jstacs.classifiers.performanceMeasures.PRCurve
- Constructs a new instance of the performance measure
PRCurve
.
- PRCurve(StringBuffer) -
Constructor for class de.jstacs.classifiers.performanceMeasures.PRCurve
- The standard constructor for the interface
Storable
.
- precompute() -
Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
- This method precomputes some normalization constant.
- precompute() -
Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
- This method precomputes some normalization constant and probabilities.
- precompute() -
Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
- This method precomputes internal fields as for instance the normalization constant.
- precompute() -
Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
-
- precompute() -
Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
-
- precomputeBurnInLength(SamplingScoreBasedClassifier.DiffSMSamplingComponent) -
Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
- Precomputes the length of the burn-in phase, e.g.
- precomputeNorm() -
Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
- Pre-computes the normalization constant.
- precomputeNormalization() -
Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
- Pre-computes all normalization constants.
- preoptimize(OptimizableFunction) -
Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
- This method allows to pre-optimize the parameter before the real optimization.
- prepareAssessment(boolean, DataSet...) -
Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
- Prepares an assessment.
- prepareThreads() -
Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
- Assigns parts of the data to the threads
- previousParameters -
Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
- The previously accepted parameters, backup for rollbacks
- prGrad -
Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.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.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
- Prints the counts and the value of this parameter to
System.out
.
- print() -
Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
- Prints the structure of this tree.
- prior -
Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
- The prior that is used in this function.
- prior -
Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
- The prior that is used in this classifier.
- PRIOR_INDEX -
Static variable in enum de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple
- This constant is the array index of the weighting factor for the prior.
- probabilities -
Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
- Represents the initial the transition probabilities.
- probs -
Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
- The parameters transformed to probabilites
- probs -
Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
- The precomputed probabilities for each possible transition.
- ProductConstraint - Class in de.jstacs.sequenceScores.differentiable.logistic
- This class implements product constraints, i.e., the method
ProductConstraint.getValue(Sequence,int)
returns the product of the values for the positions defined in the constructor. - ProductConstraint(int...) -
Constructor for class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
- This is the main constructor creating an instance from a given set of positions.
- ProductConstraint(StringBuffer) -
Constructor for class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
- This is the constructor for
Storable
.
- ProgressUpdater - Interface in de.jstacs.utils
- Interface for supervising the progress of long time processes like cross
validation.
- propagateESS(double, ArrayList<HMMFactory.PseudoTransitionElement>) -
Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
- Propagates the
ess
for an HMM with absorbing states.
- ProteinAlphabet - Class in de.jstacs.data.alphabets
- This class implements the discrete alphabet that is used for proteins (one letter code).
- ProteinAlphabet.ProteinAlphabetParameterSet - Class in de.jstacs.data.alphabets
- The parameter set for a
ProteinAlphabet
. - provideMatrix(int, int) -
Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
- This method invokes the method
AbstractHMM.createHelperVariables()
and provides the matrix with given type.
- pseudoCount -
Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
- The pseudocount for this parameter.
- PValueComputation - Class in de.jstacs.classifiers.utils
- This class can be used to compute any p-value from a given statistic.
- PValueComputation() -
Constructor for class de.jstacs.classifiers.utils.PValueComputation
-
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