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KFoldCrossValidation
from an array of
AbstractClassifier
s and a two-dimensional array of TrainableStatisticalModel
s, which are combined to additional classifiers.
KFoldCrossValidation
from a set of
AbstractClassifier
s.
KFoldCrossValidation
from a set of TrainableStatisticalModel
s.
AbstractClassifier
s and those constructed using the given
TrainableStatisticalModel
s by a KFoldCrossValidation
.
ClassifierAssessmentAssessParameterSet
that
must be used to call method assess( ...- KFoldCrossValidationAssessParameterSet() -
Constructor for class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet
- Constructs a new
KFoldCrossValidationAssessParameterSet
with empty parameter
values.
- KFoldCrossValidationAssessParameterSet(StringBuffer) -
Constructor for class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet
- The standard constructor for the interface
Storable
.
- KFoldCrossValidationAssessParameterSet(DataSet.PartitionMethod, int, boolean, int) -
Constructor for class de.jstacs.classifiers.assessment.KFoldCrossValidationAssessParameterSet
- Constructs a new
KFoldCrossValidationAssessParameterSet
with given parameter
values.
- KMereStatistic - Class in de.jstacs.motifDiscovery
- This class enables the user to get some statistics of a
DataSet
in an easy way. - KMereStatistic(DataSet, int) -
Constructor for class de.jstacs.motifDiscovery.KMereStatistic
- This constructor creates an internal statistic counting all
k
-mers in the data
.
- kruskal(double[][]) -
Static method in class de.jstacs.algorithms.graphs.MST
- Does Kruskals algorithm and finds the maximal spanning
tree (MST).
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