Artificial Immune Recognition System-Based Classification Technique

Abstract

Nowadays, data mining methods are being applied in the field of knowledge generation, which helps in decision making and intersects many disciplines of computer science such as artificial intelligence, database, statistics, visualization, and high-performance parallel computing. An artificial immune system has a set of algorithm inspired by biological immune system. This algorithm supports machine learning, and they are designed to solve difficult problems such as intrusion detection and prevention, data clustering, classification, and exploration. The proposed method focuses on executing a supervised learning algorithm AIRS, i.e., artificial immune recognition system of AIS for classification. AIRS exhibits characteristics as self-regulation, performance empirical, and parameter stability.