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Review of IDS Develepment Methods in Machine Learning

Aburomman, AbdullaIbne Reaz, Mamun Bin
International Journal of Electrical and Computer Engineering (IJECE) (Sinta 1)Vol. 0 No. 01 Oktober 2016
DOI10.11591/ijece.v6i5.pp2432-2436

Abstrak

Due to the rapid advancement of knowledge and technologies, the problem of decision making is getting more sophisticated to address, therefore the inventing of new methods to solve it is very important. One of the promising directions in machine learning and data mining is classifier combination. The popularity of this approach is confirmed by the still growing number of publications. This review paper focuses mainly on classifier combination known also as combined classifier, multiple classifier systems, or classifier ensemble. Eventually, recommendations and suggestions have also included.

Kata Kunci

Clustering, Ensemble Methods, Hybrid classifiers, IDS, Machine learning

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Review of IDS Develepment Methods in Machine Learning | International Journal of Electrical and Computer Engineering (IJECE) | Publiora