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O

offset - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.InhConstraint
This array is used to find the start indices of the conditional distributions.
offset - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
The offset of the parameter indexes
offset - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
The internally used parameter offset.
OneDataSetLogGenDisMixFunction - Class in de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix
This class implements the the following function
\[f(\underline{\lambda}|C,D,\underline{w},\underline{\alpha},\underline{\beta})
where $w_{c,n}$ is the weight for sequence $d_n$ and class $c$.
OneDataSetLogGenDisMixFunction(int, DifferentiableSequenceScore[], DataSet, double[][], LogPrior, double[], boolean, boolean) - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.OneDataSetLogGenDisMixFunction
The constructor for creating an instance that can be used in an Optimizer.
OneDimensionalFunction - Class in de.jstacs.algorithms.optimization
This class implements the interface Function for an one-dimensional function.
OneDimensionalFunction() - Constructor for class de.jstacs.algorithms.optimization.OneDimensionalFunction
 
OneDimensionalSubFunction - Class in de.jstacs.algorithms.optimization
This class is used to do the line search.
OneDimensionalSubFunction(Function) - Constructor for class de.jstacs.algorithms.optimization.OneDimensionalSubFunction
Creates a new OneDimensionalSubFunction from a Function f for the line search.
OneMinusPearsonCorrelationCoefficient() - Constructor for class de.jstacs.utils.PFMComparator.OneMinusPearsonCorrelationCoefficient
 
openRConnection(String, String, String) - Static method in class de.jstacs.utils.RUtils
This method opens an RConnection.
operationAllowed(int...) - Method in class de.jstacs.motifDiscovery.history.CappedHistory
 
operationAllowed(int...) - Method in interface de.jstacs.motifDiscovery.history.History
Returns true if the specified operation is allowed, i.e.
operationAllowed(int...) - Method in class de.jstacs.motifDiscovery.history.NoRevertHistory
 
operationAllowed(int...) - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
 
operationAllowed(int...) - Method in class de.jstacs.motifDiscovery.history.SimpleHistory
 
operationPerfomed(int...) - Method in class de.jstacs.motifDiscovery.history.CappedHistory
 
operationPerfomed(int...) - Method in interface de.jstacs.motifDiscovery.history.History
This method puts an operation to the history.
operationPerfomed(int...) - Method in class de.jstacs.motifDiscovery.history.NoRevertHistory
 
operationPerfomed(int...) - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
 
operationPerfomed(int...) - Method in class de.jstacs.motifDiscovery.history.SimpleHistory
 
OptimizableFunction - Class in de.jstacs.classifiers.differentiableSequenceScoreBased
This is the main function for the ScoreClassifier.
OptimizableFunction() - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction
 
OptimizableFunction.KindOfParameter - Enum in de.jstacs.classifiers.differentiableSequenceScoreBased
This enum defines the kinds of parameters that can be returned by the method OptimizableFunction.getParameters(KindOfParameter).
optimize(byte, DifferentiableFunction, double[], TerminationCondition, double, StartDistanceForecaster, OutputStream) - Static method in class de.jstacs.algorithms.optimization.Optimizer
This method enables you to use all different implemented optimization algorithms by only one method.
optimize(byte, DifferentiableFunction, double[], TerminationCondition, double, StartDistanceForecaster, OutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
This method enables you to use all different implemented optimization algorithms by only one method.
optimize(DifferentiableSequenceScore[], DiffSSBasedOptimizableFunction, byte, AbstractTerminationCondition, double, StartDistanceForecaster, SafeOutputStream, boolean, History, OptimizableFunction.KindOfParameter, boolean) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
This method tries to optimize the problem at hand as good as possible.
optimize(DifferentiableSequenceScore[], DiffSSBasedOptimizableFunction, byte, AbstractTerminationCondition, double, StartDistanceForecaster, SafeOutputStream, boolean, History[][], int[][], OptimizableFunction.KindOfParameter, boolean) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
This method tries to optimize the problem at hand as good as possible.
optimizeHidden - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
This boolean indicates whether to optimize the hidden variables of this instance.
optimizeModel - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
A switch for each model whether to optimize/adjust or not.
Optimizer - Class in de.jstacs.algorithms.optimization
This class can be used for optimization purposes.
Optimizer() - Constructor for class de.jstacs.algorithms.optimization.Optimizer
 
order - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
The order of the tensor.
order - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
The network structure, used internally.
order - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
The order of the model.
order(double[], boolean) - Static method in class de.jstacs.utils.ToolBox
This method computes the order of the elements to obtain a sorted array.
original - Variable in class de.jstacs.data.sequences.MappedDiscreteSequence
The original Sequence.
originalAlphabetContainer - Variable in class de.jstacs.data.sequences.MappedDiscreteSequence
The original AlphabetContainer.
overlaps(LocatedSequenceAnnotationWithLength) - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
Returns true if this LocatedSequenceAnnotationWithLength overlaps with the location of second.
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