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Parameter
s in this ParameterSet
by their
equivalents implementing the Rangeable
interface.
MappingClassifier
from a given classifier and a
class mapping.
Storable
.
Sample
s to the internal classes.
w
between index start
and end
.
NumericalResultSet
s.MeanResultSet
with an empty set of
NumericalResultSet
s.
MeanResultSet
with an empty set of
NumericalResultSet
s and no further information.
Storable
.
MeanResultSet
s
should be added that do not match.MeanResultSet.AdditionImpossibleException
with an
appropriate error message.
NumericalResultSet
is
added to the MeanResultSet
that has a number of results which is
not equal to the number of results of the previously added results.MeanResultSet.InconsistentResultNumberException
with an
appropriate error message.
evaluate
-methods of a
classifier.MeasureParameters
.
MeasureParameters
.
MeasureParameters
.
Storable
.
enum
defines all measures that are currently
implemented in Jstacs.MEMConstraint
as part of a (whole) model.
MEMConstraint
as part of a model.
Storable
.
Model
s.MixtureModel
.
Storable
.
MixtureScoringFunction
.
Storable
.
Model
s and
clones these if necessary.
Model
s.
Storable
.
Model
s.
AlphabetContainer
.
motifIndex
.
motifIndex
.
StrandedLocatedSequenceAnnotationWithLength
that is a
motif.MotifAnnotation
of type type
with
identifier identifier
and additional annotation (that does
not fit the SequenceAnnotation
definitions) given as an array of
Result
s additionalAnnotation
.
Storable
.
enum
can be used to determine which kind of profile
should be returned.MotifDiscoverer
.MRFScoringFunction
with
equivalent sample size (ess) 0.
MRFScoringFunction
.
Storable
.
start
to
end
with the value factor
.
\lambda
at position
index
with the factor val
:
\exp(\lambda_{index}) * val
.
Parameter
that provides a collection of possible values.MultiSelectionCollectionParameter
.
MultiSelectionCollectionParameter
.
MultiSelectionCollectionParameter
from an array of
ParameterSet
s.
MultiSelectionCollectionParameter
from an array of
ParameterSet
s.
Storable
.
MultiSelectionCollectionParameter
from the
necessary field.
NormalizableScoringFunction
for an inhomogeneous Markov model.Storable
.
MutableMotifDiscoverer
.MutableMotifDiscovererToolbox.getSortedInitialParameters(Sample[], ScoringFunction[], InitMethodForScoringFunction[], OptimizableFunction, int, SafeOutputStream)
.
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