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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".
Sequence
s, of the
DataSet
in two distinct parts.
Sequence
s, of the
DataSet
in distinct parts where each part holds the corresponding
percentage given in the array percentage
.
Sequence
s, of the
DataSet
and the corresponding weights in distinct parts where each part holds the corresponding
percentage given in the array percentage
.
Sequence
s, of the
DataSet
in k
distinct parts.
Sequence
s, of the
DataSet
and the corresponding weights in k
distinct parts.
AbstractPerformanceMeasure
s that can be used
in AbstractClassifier.evaluate(PerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...)
.Storable
.
PerformanceMeasureParameterSet
that can be used for binary classifiers.
PerformanceMeasureParameterSet
that can be used for classifiers that
handle the given number of classes.
PerformanceMeasureParameterSet
with the given performance measures.
selection
that can be used for classifiers handling a given number of classes.
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.
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.
- 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. useful for computing scores of
multiple sequences
- 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(DataSet...) -
Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
- Prepares an assessment.
- 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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