Abstract: Genetic programming (GP) has emerged as a promising approach to deal with the classification task in data mining. This paper extends the tree ...

rules list is use to predict a new instance, the best rule will be considered first. If the rule does not match the instance, i.e.,.

Genetic programming (GP) has emerged as a promising approach to deal with the classification task in data mining. This paper extends the tree representation ...

This paper introduces a new Grammar-Guided Genetic Programming algorithm for resolving multi-instance learning problems. This algorithm, called G3P-MI, is ...

Mining multiple comprehensible classification rules using genetic programming. Created by W.Langdon from gp-bibliography.bib Revision:1.7764.

This work extends the tree representation of GP to evolve multiple comprehensible IF-THEN classification rules. In the paper, we introduce a concept mapping ...

Abstract. Data mining deals with the problem of discovering novel and interesting knowledge from large amount of data. This.

A classification algorithm based on genetic algorithms (GAs) that discovers comprehensible IF-THEN rules, in the spirit of data mining is presented.

Using these measures as the objectives of rule mining problem, this paper uses gene expression programming to extract some useful and understandable rule.

Abstract—In this paper, Genetic Programming is used to evolve ordered rule sets (also called decision lists) for a number of benchmark classification ...