Skip to search formSkip to main contentSkip to account menu

Rule induction

Known as: Rule extraction, Rule learning 
Rule induction is an area of machine learning in which formal rules are extracted from a set of observations. The rules extracted may represent a… 
Wikipedia (opens in a new tab)

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Attribute reduction is one of the most important problems in rough set theory. However, in real-world lots of information systems… 
Highly Cited
2005
Highly Cited
2005
A method of association rule mining using genetic network programming (GNP) is proposed to improve the performance of association… 
Highly Cited
1999
Highly Cited
1999
This paper deals with an evaluation and comparison of the accuracy and complexity of symbolic rules extracted from radial basis… 
Highly Cited
1998
Highly Cited
1998
Objective function‐based fuzzy clustering aims at finding a fuzzy partition by optimizing a function that evaluates a (fuzzy… 
Highly Cited
1993
Highly Cited
1993
Swap-1, a state-of-the-art system for learning decision rules from data, is presented. The method embodied in Swap-1 generates… 
Highly Cited
1991
Highly Cited
1991
A fuzzy rule extraction method from a multilayered neural network is proposed to realize the multiplicative merits of neural and…