Evolutionary Induction of Descriptive Rules in a Market Problem

Abstract

Abstract. Nowadays, face to face contact with the client continues to be fundamental to the development of marketing acts. Trade fairs are, in this sense, a basic instrument in company marketing policies, especially in Industrial Marketing. Due to the elevated investment in term of both time and money it is necessary the automatic extraction of relevant and interesting information which helps to improve fair planning policies.In this paper, we analyse this problem and the kind of knowledge the user is interested in. We study the use of Soft Computing methodologies, specifically Fuzzy Logic and Genetic Algorithms, in the design of the Data Mining algorithms most proper to this problem, descriptive induction algorithms for subgroup discovery. Then we present an evolutionary model for the descriptive induction of fuzzy or crisp rules which describe subgroups. The proposal includes a GA in an iterative model which extracts rules while examples are left uncovered and the rules obtained surpass an specified confidence level.

Evolutionary multi objective optimization for rule mining: a review

“…Del Jesus et al (2005) state that the application of a GA to solve a problem must determine: (a) A genetic representation of the search space (called genotype) and of the solutions of the problem (called phenotype); (b) A way to create an initial population of solutions; (c) An evaluation or fitness function which provides a quality value to each chromosome; (d) Operators which modify the genetic composition of the descendants during reproduction; and (e) Values for the parameters used (population size, probabilities of application of genetic operators, etc. ).…”