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K

kappa(). Method in class weka.classifiers.Evaluation
Returns value of kappa statistic if class is nominal.
KBInformation(). Method in class weka.classifiers.Evaluation
Return the total Kononenko & Bratko Information score in bits
KBMeanInformation(). Method in class weka.classifiers.Evaluation
Return the Kononenko & Bratko Information score in bits per instance.
KBRelativeInformation(). Method in class weka.classifiers.Evaluation
Return the Kononenko & Bratko Relative Information score
KDConditionalEstimator class weka.estimators.KDConditionalEstimator.
Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).
KDConditionalEstimator(int, double). Constructor for class weka.estimators.KDConditionalEstimator
Constructor
KernelDensity class weka.classifiers.KernelDensity.
Class for building and using a very simple kernel density classifier.
KernelDensity(). Constructor for class weka.classifiers.KernelDensity
KernelEstimator class weka.estimators.KernelEstimator.
Simple kernel density estimator.
KernelEstimator(double). Constructor for class weka.estimators.KernelEstimator
Constructor that takes a precision argument.
key. Variable in class weka.classifiers.kstar.KStarCache.TableEntry
attribute value
keyFieldNameTipText(). Method in class weka.experiment.AveragingResultProducer
Returns the tip text for this property
KKConditionalEstimator class weka.estimators.KKConditionalEstimator.
Conditional probability estimator for a numeric domain conditional upon a numeric domain.
KKConditionalEstimator(double). Constructor for class weka.estimators.KKConditionalEstimator
Constructor
KStar class weka.classifiers.kstar.KStar.
K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by some similarity function.
KStar(). Constructor for class weka.classifiers.kstar.KStar
KStarCache class weka.classifiers.kstar.KStarCache.
A class representing the caching system used to keep track of each attribute value and its corresponding scale factor or stop parameter.
KStarCache.CacheTable class weka.classifiers.kstar.KStarCache.CacheTable.
A custom hashtable class to support the caching system.
KStarCache.CacheTable(KStarCache). Constructor for class weka.classifiers.kstar.KStarCache.CacheTable
Constructs a new hashtable with a default capacity and load factor.
KStarCache.CacheTable(KStarCache, int, float). Constructor for class weka.classifiers.kstar.KStarCache.CacheTable
Constructs a new hashtable with a default capacity and load factor.
KStarCache.TableEntry class weka.classifiers.kstar.KStarCache.TableEntry.
Hashtable collision list.
KStarCache.TableEntry(KStarCache, int, double, double, double, KStarCache.TableEntry). Constructor for class weka.classifiers.kstar.KStarCache.TableEntry
Constructor
KStarCache(). Constructor for class weka.classifiers.kstar.KStarCache
KStarConstants interface weka.classifiers.kstar.KStarConstants.
KStarNominalAttribute class weka.classifiers.kstar.KStarNominalAttribute.
A custom class which provides the environment for computing the transformation probability of a specified test instance nominal attribute to a specified train instance nominal attribute.
KStarNominalAttribute(Instance, Instance, int, Instances, int[][], KStarCache). Constructor for class weka.classifiers.kstar.KStarNominalAttribute
Constructor
KStarNumericAttribute class weka.classifiers.kstar.KStarNumericAttribute.
A custom class which provides the environment for computing the transformation probability of a specified test instance numeric attribute to a specified train instance numeric attribute.
KStarNumericAttribute(Instance, Instance, int, Instances, int[][], KStarCache). Constructor for class weka.classifiers.kstar.KStarNumericAttribute
Constructor
KStarWrapper class weka.classifiers.kstar.KStarWrapper.
KStarWrapper(). Constructor for class weka.classifiers.kstar.KStarWrapper

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