Feature selection using cloud-based parallel genetic algorithm for intrusion detection data classification

With the exponential growth of the amount of data being generated, stored and processed on a daily basis in the machine learning, data analytics and decision-making systems, the data preprocessing established itself as the key factor for building reliable high-performance machine learning models. On...

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Veröffentlicht in:	Neural computing & applications Jg. 33; H. 18; S. 11861 - 11873
Hauptverfasser:	Mehanović, Dželila, Kečo, Dino, Kevrić, Jasmin, Jukić, Samed, Miljković, Adnan, Mašetić, Zerina
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.09.2021 Springer Nature B.V
Schlagworte:	Artificial Intelligence Artificial neural networks Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Datasets Decision analysis Decision making Decision trees Feature selection Genetic algorithms Image Processing and Computer Vision Learning theory Machine learning Original Article Parallel processing Preprocessing Probability and Statistics in Computer Science Support vector machines Parallel genetic algorithm Feature selection Machine learning Intrusion detection systems
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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