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Storable interface.
true all used alphabets ignore the case.
true the alphabet ignores the case.
IntLists that are used while computing the partial derivation
ImageResult from a BufferedImage.
Storable.
Storable.
BayesianNetworkScoringFunction that is an inhomogeneous Markov model.order.
InhomogeneousMarkov structure from its XML-representation as returned by InhomogeneousMarkov.toXML().
Parameters in this ParameterSet.
ParameterTree randomly
Parameters,
which is a ParameterSet.ParameterList.
Parameters,
which is a ParameterSet.ParameterList, with an initial number of Parameters
of initCapacity.
AlphabetContainer by incorporating additional alphabets
into an exsisting AlphabetContainer.
probs.
ParameterSet containing all parameters necessary to construct an
Object that implements InstantiableFromParameterSet.InstanceParameterSet having empty parameter values.
InstanceParameterSet having empty parameter values.
InstanceParameterSet from its XML-representation.
InstanceParameterSet from the alphabet and the length.
InstanceParameterSet for an object that can handle sequences of variable length and with the alphabet.
ParameterSet.size.
IntronAnnotation from a donor SinglePositionSequenceAnnotation and an acceptor SinglePositionSequenceAnnotation and a set of additional annotations.
IntronAnnotation from its XML-representation as returned by LocatedSequenceAnnotationWithLength.toXML().
Model.emitSample(int, int...).
delim.
ParameterSet contains only atomic
parameters, i.e. the parameters do not contain ParameterSets
themselves.
NullProgressUpdater.
true if the datatype of test can be casted to that of this instance and both have the same name and
comment for the result.
true if test and the current object have the same datatype, name and
comment for the result.
true all postions use discrete values.
true all postions use DiscreteAlphabetParameterSets.
true if position pos is a discrete random variable.
true all positions use discrete values.
true if continuous is a symbol of the alphabet used in position
pos.
true if candidat is an element of the internal interval.
true if candidate is an element of the internal interval.
true if the object is currently used in a sampling, otherwise
false.
true if the object is currently used in a sampling, otherwise
false.
ParameterTree is a leaf, i.e. it has no children in the network structure of the
enclosing BayesianNetworkScoringFunction.
true if the parameter is required, false otherwise
sel is selected.
key
true if the option at position idx is selected.
Measure supports shifts.
true all postions use the same alphabet.
true.
TRUE if the model or classifier was trained when obtaining its XML-representation
stored in this ObjectResult, FALSE if it was not, and NA
if the object could not be trained anyway.
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