- 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

where

is the weight for sequence

and class

.
- 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
-
- OneMinusPearsonCorrelationCoefficient() - Constructor for class de.jstacs.utils.PFMComparator.OneMinusPearsonCorrelationCoefficient
-
- openRConnection(String, String, String) - Static method in class de.jstacs.utils.RUtils
-
- 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
-
- OptimizableFunction() - Constructor for class de.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction
-
- OptimizableFunction.KindOfParameter - Enum in de.jstacs.classifiers.differentiableSequenceScoreBased
-
- 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
-
- originalAlphabetContainer - Variable in class de.jstacs.data.sequences.MappedDiscreteSequence
-
- overlaps(LocatedSequenceAnnotationWithLength) - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
-