Package

weka.classifiers.lazy

Synopsis

K-nearest neighbours classifier. Can select appropriate value of K based on cross-validation. Can also do distance weighting.

For more information, see

D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.

The table below describes the options available for IBk.

Option	Description
KNN	The number of neighbours to use.
crossValidate	Whether hold-one-out cross-validation will be used to select the best k value.
debug	If set to true, classifier may output additional info to the console.
distanceWeighting	Gets the distance weighting method used.
meanSquared	Whether the mean squared error is used rather than mean absolute error when doing cross-validation for regression problems.
nearestNeighbourSearchAlgorithm	The nearest neighbour search algorithm to use (Default: weka.core.neighboursearch.LinearNNSearch).
windowSize	Gets the maximum number of instances allowed in the training pool. The addition of new instances above this value will result in old instances being removed. A value of 0 signifies no limit to the number of training instances.

The table below describes the capabilites of IBk.

Capability	Supported
Class	Nominal class, Missing class values, Date class, Numeric class, Binary class
Attributes	Date attributes, Unary attributes, Empty nominal attributes, Numeric attributes, Nominal attributes, Binary attributes, Missing values
Min # of instances	0