IBk
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 |