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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.

Options

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.

Capabilities

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

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