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On the Use of Vgs for Feature Selection in Supervised Machine Learning - A Use Case to Detect Distributed Dos Attacks

AuthID
P-010-1SF

Author(s)

Lopes, J

Partida, A

Pinto, P

Pinto, A

Editor(es)

Pereira,AI;Mendes,A;Fernandes,FP;Pacheco,MF;Coelho,JP;Lima,J

Tipo de Documento

Proceedings Paper

Year published

2024

Publicado

in OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, PT I, OL2A 2023 in Communications in Computer and Information Science, ISSN: 1865-0929

Volume: 1981, Páginas: 269-283 (15)

Conference

3Rd International Conference on Optimization, Learning Algorithms and Applications (Ol2A), Date: SEP 27-29, 2023, Location: Ponta Delgada, PORTUGAL

Indexing

Wos^®

Dblp^®/pt/publications/view/1050415

Crossref^®

Google Scholar^®

Metadata
Fontes

Publication Identifiers

DOI: 10.1007/978-3-031-53025-8_19

DBLP: conf/ol2a/LopesP0P23

Wos: WOS:001264653200019

Source Identifiers

ISSN: 1865-0929

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On the Use of Vgs for Feature Selection in Supervised Machine Learning - A Use Case to Detect Distributed Dos Attacks

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On the Use of Vgs for Feature Selection in Supervised Machine Learning - A Use Case to Detect Distributed Dos Attacks

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