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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 from the corresponding InstanceParameterSet parameters.
InhomogeneousMarkov structure from its XML-representation as returned by InhomogeneousMarkov.toXML().
InstanceParameterSet that defines the parameters of a InhomogeneousMarkov structure Measure.InhomogeneousMarkov.InhomogeneousMarkovParameterSet with empty parameter values.
InhomogeneousMarkov.InhomogeneousMarkovParameterSet with the parameter for the order set to order
InhomogeneousMarkov.InhomogeneousMarkovParameterSet from its XML-representation as defined by
the Storable interface.
Parameters in this
ClassifierAssessmentAssessParameterSet.
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 existing
AlphabetContainer.
probs.
Parameters that can be used to instantiate another class.InstanceParameterSet from the class that can be instantiated using
this InstanceParameterSet.
InstanceParameterSet out of an XML representation
InstanceParameterSet.Sample containing only sequences that are
contained in all Samples of the array.
int.IntList with
initial length 10.
IntList with
initial length 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().
AlphabetContainer with alphabets
that use a huge number of symbols.Model.emitSample(int, int...).
delim.
SymbolExtractor.
ParameterSet contains only atomic
parameters, i.e. the parameters do not contain ParameterSets
themselves.
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 positions use discrete
values.
true all positions use
DiscreteAlphabet.DiscreteAlphabetParameterSets.
true if position pos is a discrete
random variable.
true if 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
AlphabetContainer also
computes the reverse complement of a sequence.
true if the option sel is selected.
key
true if the option at position idx is selected.
Measure supports shifts.
true all positions 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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