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## K

KFoldCrossValidation - Class in de.jstacs.classifier.assessment
  This class implements a k-fold crossvalidation.
KFoldCrossValidation(AbstractClassifier[], Model[][], boolean, boolean) - Constructor for class de.jstacs.classifier.assessment.KFoldCrossValidation
  Creates a new `KFoldCrossValidation` from an array of `AbstractClassifier`s and a two-dimensional array of `Model` s, which are combined to additional classifiers.
KFoldCrossValidation(AbstractClassifier...) - Constructor for class de.jstacs.classifier.assessment.KFoldCrossValidation
  Creates a new `KFoldCrossValidation` from a set of `AbstractClassifier`s.
KFoldCrossValidation(boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.KFoldCrossValidation
  Creates a new `KFoldCrossValidation` from a set of `Model`s.
KFoldCrossValidation(AbstractClassifier[], boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.KFoldCrossValidation
  This constructor allows to assess a collection of given `AbstractClassifier`s and those constructed using the given `AbstractModel`s by a `KFoldCrossValidation`.
KFoldCVAssessParameterSet - Class in de.jstacs.classifier.assessment
  This class implements a `ClassifierAssessmentAssessParameterSet` that must be used to call method `assess( ... )` of a `KFoldCrossValidation`.
KFoldCVAssessParameterSet() - Constructor for class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
  Constructs a new `KFoldCVAssessParameterSet` with empty parameter values.
KFoldCVAssessParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
  Constructs a `KFoldCVAssessParameterSet` out of an XML representation.
KFoldCVAssessParameterSet(Sample.PartitionMethod, int, boolean, int) - Constructor for class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
  Constructs a new `KFoldCVAssessParameterSet` with given parameter values.
kruskal(double[][]) - Static method in class de.jstacs.algorithms.graphs.MST
  Does Kruskals algorithm and finds the maximal spanning tree.

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