LBR

Package

weka.classifiers.lazy

Synopsis

Lazy Bayesian Rules Classifier. The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. Lazy Bayesian Rules selectively relaxes the independence assumption, achieving lower error rates over a range of learning tasks. LBR defers processing to classification time, making it a highly efficient and accurate classification algorithm when small numbers of objects are to be classified.

For more information, see:

Zijian Zheng, G. Webb (2000). Lazy Learning of Bayesian Rules. Machine Learning. 4(1):53-84.

Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (lazyBayesianRules).

Options

The table below describes the options available for LBR.

Capabilities

The table below describes the capabilites of LBR.