A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

K

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

KDDataGenerator - class weka.gui.boundaryvisualizer.KDDataGenerator.

KDDataGenerator.

KDDataGenerator() - Constructor for class weka.gui.boundaryvisualizer.KDDataGenerator

KEY_SIZE - Static variable in class weka.experiment.ClassifierSplitEvaluator

The length of a key

KEY_SIZE - Static variable in class weka.experiment.RegressionSplitEvaluator

The length of a key

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

KNNTipText() - Method in class weka.classifiers.lazy.IBk

Returns the tip text for this property

KNNTipText() - Method in class weka.classifiers.lazy.LWL

Returns the tip text for this property

KStar - class weka.classifiers.lazy.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.lazy.KStar

KStarCache - class weka.classifiers.lazy.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() - Constructor for class weka.classifiers.lazy.kstar.KStarCache

KStarCache.CacheTable - class weka.classifiers.lazy.kstar.KStarCache.CacheTable.

A custom hashtable class to support the caching system.

KStarCache.CacheTable(int, float) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Constructs a new hashtable with a default capacity and load factor.

KStarCache.CacheTable() - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable

Constructs a new hashtable with a default capacity and load factor.

KStarCache.TableEntry - class weka.classifiers.lazy.kstar.KStarCache.TableEntry.

Hashtable collision list.

KStarCache.TableEntry(int, double, double, double, KStarCache.TableEntry) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.TableEntry

Constructor

KStarConstants - interface weka.classifiers.lazy.kstar.KStarConstants.

KStarNominalAttribute - class weka.classifiers.lazy.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.lazy.kstar.KStarNominalAttribute

Constructor

KStarNumericAttribute - class weka.classifiers.lazy.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.lazy.kstar.KStarNumericAttribute

Constructor

KStarWrapper - class weka.classifiers.lazy.kstar.KStarWrapper.

KStarWrapper() - Constructor for class weka.classifiers.lazy.kstar.KStarWrapper

KValueTipText() - Method in class weka.classifiers.trees.RandomTree

Returns the tip text for this property

Kernel - class weka.classifiers.functions.supportVector.Kernel.

Abstract kernel.

Kernel() - Constructor for class weka.classifiers.functions.supportVector.Kernel

KernelEstimator - class weka.estimators.KernelEstimator.

Simple kernel density estimator.

KernelEstimator(double) - Constructor for class weka.estimators.KernelEstimator

Constructor that takes a precision argument.

KnowledgeFlow - class weka.gui.beans.KnowledgeFlow.

Main GUI class for the KnowledgeFlow

KnowledgeFlow() - Constructor for class weka.gui.beans.KnowledgeFlow

Creates a new KnowledgeFlow instance.

KnowledgeFlow.BeanLayout - class weka.gui.beans.KnowledgeFlow.BeanLayout.

Used for displaying the bean components and their visible connections

KnowledgeFlow.BeanLayout() - Constructor for class weka.gui.beans.KnowledgeFlow.BeanLayout

KononenkosMDL(double[], double[][], double, int) - Method in class weka.filters.supervised.attribute.Discretize

Test using Kononenko's MDL criterion.

k_MarginResolution - Static variable in class weka.classifiers.Evaluation

Resolution of the margin histogram

kappa() - Method in class weka.classifiers.Evaluation

Returns value of kappa statistic if class is nominal.

keepLastModel() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost.Committee

key - Variable in class weka.attributeSelection.ConsistencySubsetEval.hashKey

The key

key - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry

attribute value

key - Variable in class weka.classifiers.rules.DecisionTable.hashKey

The key

keyFieldNameTipText() - Method in class weka.experiment.AveragingResultProducer

Returns the tip text for this property