Package
weka.classifiers.rules
Synopsis
Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes. For more information, see:
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
Options
The table below describes the options available for OneR.
Option | Description |
|---|---|
debug | If set to true, classifier may output additional info to the console. |
minBucketSize | The minimum bucket size used for discretizing numeric attributes. |
Capabilities
The table below describes the capabilites of OneR.
Capability | Supported |
|---|---|
Class | Binary class, Missing class values, Nominal class |
Attributes | Numeric attributes, Binary attributes, Nominal attributes, Unary attributes, Missing values, Date attributes, Empty nominal attributes |
Min # of instances | 1 |