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KFoldCrossValidation from an array of
AbstractClassifiers and a two-dimensional array of TrainableStatisticalModel
s, which are combined to additional classifiers.
KFoldCrossValidation from a set of
AbstractClassifiers.
KFoldCrossValidation from a set of TrainableStatisticalModels.
AbstractClassifiers and those constructed using the given
TrainableStatisticalModels 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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