Automatic Generation of Meta Classifiers with Large Levels for Distributed Computing and Networking

• Published in: Journal of networks Vol. 9; no. 9; p. 2259
• Main Authors: Abawajy, Jemal, Kelarev, Andrei, Chowdhury, Morshed
• Format: Journal Article
• Language: English
• Published: Oulu Academy Publisher 01.09.2014
• Subjects: Classification; Classifiers; Construction; Electronic mail; Email; Filtering; Filtration; Phishing
• ISSN: 1796-2056; 1796-2056
• DOI: 10.4304/jnw.9.9.2259-2268

This paper is devoted to a case study of a new construction of classifiers. These classifiers are called automatically generated multi-level meta classifiers (AGMLMC). The AGMLMC classifiers are unified classifiers with many parts that can operate in parallel. This paper introduces new construction of classifiers and undertakes an experimental study of their performance. The authors look at a case study of their effectiveness in the special case of the detection and filtering of phishing emails. This is a possible important application area for such large and distributed classification systems. The experiments investigate the effectiveness of combining diverse meta classifiers into one AGMLMC classifier in the case study of detection and filtering of phishing emails. The results show that new classifiers with large levels achieved better performance compared to the base classifiers and simple meta classifiers classifiers. This demonstrates that the new technique can be applied to increase the performance if diverse meta classifiers are included in the system.