This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. A paramount work, its 800 entries - about 150 of...
This paper presents selected data mining techniques that can be applied in medicine, and in particular some machine learning techniques including the mechanisms that make them better suited for the...doi:10.1016/j.neucom.2017.09.027Hamid Alinejad-Rokny...
This authoritative, expanded and updated third edition ofEncyclopedia of Machine Learning and Data Miningprovides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. A paramount work, its 1000 entries – over 200 of th...
IoT shallow machine learning deep learning data science IDS 1. Introduction Internet of things (IoT) are growing exponentially and playing a vital role in our everyday life. IoT nodes can use internet protocol address and connect to internet. These self-configured smart nodes are driving beyond ...
data are processed for machine learning analysis and highlight the current challenges in furthering intelligent solutions in the IoT environment. Furthermore, we propose a framework to enable IoT applications to adaptively learn from other IoT applications and present a case study in how the ...
learning-based feed-forward neural network algorithm's accuracy, precision, recall, and F-measure across three vital datasets: NSL-KDD, UNSW-NB 15, and CICIDS 2017, considering both full and reduced feature sets. Comparative analysis against benchmark machine learning approaches is also conducted. ...
NB is a practical yet straightforward machine learning algorithm used for predictive modeling99. It relies on the assumption that the presence of one feature within a class is independent of the others, which is why it is called “naïve.” Grounded in Bayes’ theorem, this technique often yi...
His field of interest is mainly in AI, machine learning, deep learning, image processing, soft computing, bioinformatics, IoT, data mining. Jyotsna Kumar Mandal obtained his PhD in CSE from Jadavpur University He has more than 450 publications in reputed international journals and conferences. ...
machine learning to zero-day attack detection Mohanad Sarhan1 · Siamak Layeghy1 · Marcus Gallagher1 · Marius Portmann1 Published online: 15 March 2023 © The Author(s) 2023 Abstract Machine learning (ML) models have proved efficient in classifying data samples into their respective categories...
Doshi R, Apthorpe N, Feamster N (2018) Machine learning ddos detection for consumer internet of things devices. In: 2018 IEEE security and privacy workshops (SPW). IEEE, pp 29–35 Dua S, Du X (2016) Data mining and machine learning in cybersecurity. CRC Press, Boca Raton Book MATH Go...