|Rule learning is a machine learning technique that induce
a target function from examples. The target function is defined jointly
as a set of if-then rules.
The technique has established itself a basic component of many machine learning systems, and has been the first machine learning technology to deliver commercially successful applications (e.g. GASOIL, BMT, in process control...).
This web site only introduces an algorithm in Rule Learing family, namely CN2, in top-down approach. It contains the following documents:
Sequential Covering is the most popular algorithm that rule learning employs. It learns a single rule each time, repeats process untill the final set is formed.
CN2 is one of variation of sequantial covering to be discussed here. It learns rules for all classes, and it can handle noises.
An Applet demostrating CN2 in action with a given example.