Hybrid Fuzzy Jordan Network for Robust and Efficient Intrusion Detection System

Dhivya, A.; Sivanandan, Srinivasan

doi:10.17485/ijst/2015/v8i34/76697

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Hybrid and Ensemble Pattern Recognition1

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2016

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Cited by 3 publications

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“…In literature, several approaches for classifiers combination proposed. [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21], [22,23,24,25,26,27,28,29,30,31]…”

Section: Hybrid and Ensemble Pattern Recognitionmentioning

confidence: 99%

Review of IDS Develepment Methods in Machine Learning

Aburomman

Reaz

2016

IJECE

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<p>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.</p>

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“…In literature, several approaches for classifiers combination proposed. [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21], [22,23,24,25,26,27,28,29,30,31]…”

Section: Hybrid and Ensemble Pattern Recognitionmentioning

confidence: 99%