New Discrete Crow Search Algorithm for Class Association Rule Mining

作     者：Hichem, Haouassi Mehdaoui, Rafik Ouahiba, Chouhal 

作者机构：Univ Abbas Laghrour ICOSI Lab Khenchela Algeria 

出 版 物：《INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH》 (国际群智能研究杂志)

年 卷 期：2022年第13卷第1期

页      面：1-21页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Associative Classification Classification Data Mining Discrete Crow Search Algorithm Meta-Heuristic Rule-Based Classification Swarm-Based Optimization 

摘      要：Associative classification (AC) or class association rule (CAR) mining is a very efficient method for the classification problem. It can build comprehensible classification models in the form of a list of simple IF-THEN classification rules from the available data. In this paper, the authors present a new and improved discrete version of the crow search algorithm (CSA) called NDCSA-CAR to mine the class association rules. The goal of this article is to improve the data classification accuracy and the simplicity of classifiers. The authors applied the proposed NDCSA-CAR algorithm on 11 benchmark datasets and compared its result with traditional algorithms and recent well known rule-based classification algorithms. The experimental results show that the proposed algorithm outperformed other rule-based approaches in all evaluated criteria.