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element1 and element2.
Strings.Strings 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
Parameters.ParameterSet with empty parameter values.
ParameterSet out of an array of Parameters.
ParameterSet out of an ArrayList of
Parameters.
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.
Parameters and creates instances of
InstantiableFromParameterSets 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.ParameterSets.
Map.Entry that sorts by the key of the Map.Entry.Comparator that only compares the keys of Map.Entrys.
Map.Entry where value is a ComparableElement with weight Integer.Comparator that only compares the ranks of Map.Entrys 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
SequenceAnnotations 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 Integers.
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.AbstractPerformanceMeasures 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 PhyloNodes that represent the children nodesStorable.
Storable.
AbstractScoreBasedClassifier.DoubleTableResults 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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