abawajy-automaticgeneration-2014.pdf (1.3 MB)
Automatic generation of meta classifiers with large levels for distributed computing and networking
journal contribution
posted on 2014-09-07, 00:00 authored by Jemal AbawajyJemal Abawajy, Andrei Kelarev, Morshed ChowdhuryMorshed ChowdhuryThis 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 NetworksVolume
9Issue
9Pagination
2259 - 2268Publisher
Academy PublisherLocation
Oulu, FinlandPublisher DOI
ISSN
1796-2056Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, Academy PublisherUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC