Algorithms for clustering data
Algorithms for clustering data
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management
A Dual-Objective Evolutionary Algorithm for Rules Extraction in Data Mining
Computational Optimization and Applications
Data Mining: A Knowledge Discovery Approach
Data Mining: A Knowledge Discovery Approach
A hybrid PSO/ACO algorithm for discovering classification rules in data mining
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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This paper provides a memetic approach in order to extract comprehensible and accurate classification rules. Indeed to construct a model of classification we need to extract not only accurate rules but comprehensible also, to help the human interpretation of the model and the decision make process. In this paper we describe a purely genetic approach, then a tabu search approach and finaly a memetic algorithm to extract classification rules. The memetic approach is a hybridization of a genetic algorithm and a local search based on a tabu search algorithm. Many conducted tests on the well-known UCI (University of California Irvine) benchmarks are presented and a comparative study of the obtained results with the three approaches is also presented. The paper will conclude by giving a discussion on the obtained results for the three approaches and some future works.