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Automatic generation of meta classifiers with large levels for distributed computing and networking

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journal contribution
posted on 2014-09-07, 00:00 authored by Jemal AbawajyJemal Abawajy, Andrei Kelarev, Morshed ChowdhuryMorshed Chowdhury
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 construction combines diverse meta classifiers in a new way to create a unified system. This original construction can be generated automatically producing classifiers with large levels. Different meta classifiers are incorporated as low-level integral parts of another meta classifier at the top level. It is intended for the distributed computing and networking. The AGMLMC classifiers are unified classifiers with many parts that can operate in parallel. This make it easy to adopt them in distributed applications. This paper introduces new construction of classifiers and undertakes an experimental study of their performance. We 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. Our 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.

History

Journal

Journal of Networks

Volume

9

Pagination

2259-2268

Location

Oulu, Finland

Open access

  • Yes

ISSN

1796-2056

Language

eng

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2014, Academy Publisher

Issue

9

Publisher

Academy Publisher