On hyperparameter optimization of machine learning algorithms: Theory and practice

L Yang, A Shami - Neurocomputing, 2020‏ - Elsevier
Abstract Machine learning algorithms have been used widely in various applications and
areas. To fit a machine learning model into different problems, its hyper-parameters must be …

Classification technique and its combination with clustering and association rule mining in educational data mining—A survey

SM Dol, PM Jawandhiya - Engineering applications of artificial intelligence, 2023‏ - Elsevier
Educational data mining (EDM) is the application of data mining in the educational field.
EDM is used to classify, analyze, and predict the students' academic performance, and …

MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles

L Yang, A Moubayed, A Shami - IEEE Internet of Things Journal, 2021‏ - ieeexplore.ieee.org
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …

Multi-stage optimized machine learning framework for network intrusion detection

MN Injadat, A Moubayed, AB Nassif… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …

Machine learning towards intelligent systems: applications, challenges, and opportunities

MN Injadat, A Moubayed, AB Nassif… - Artificial Intelligence …, 2021‏ - Springer
The emergence and continued reliance on the Internet and related technologies has
resulted in the generation of large amounts of data that can be made available for analyses …

Predicting student academic performance at higher education using data mining: a systematic review

SA Alwarthan, N Aslam, IU Khan - … Intelligence and Soft …, 2022‏ - Wiley Online Library
Recently, educational institutions faced many challenges. One of these challenges is the
huge amount of educational data that can be used to discover new insights that have a …

Detecting botnet attacks in IoT environments: An optimized machine learning approach

MN Injadat, A Moubayed… - 2020 32nd International …, 2020‏ - ieeexplore.ieee.org
The increased reliance on the Internet and the corresponding surge in connectivity demand
has led to a significant growth in Internet-of-Things (IoT) devices. The continued deployment …

[PDF][PDF] Artificial Neural Network Hyperparameters Optimization: A Survey.

ZS Kadhim, HS Abdullah, KI Ghathwan - Int. J. Online Biomed. Eng., 2022‏ - academia.edu
Machine-learning (ML) methods often utilized in applications like computer vision,
recommendation systems, natural language processing (NLP), as well as user behavior …

Imbalanced classification methods for student grade prediction: A systematic literature review

SDA Bujang, A Selamat, O Krejcar, F Mohamed… - IEEE …, 2022‏ - ieeexplore.ieee.org
Student success is essential for improving the higher education system student outcome.
One way to measure student success is by predicting students' performance based on their …

An explainable model for identifying at-risk student at higher education

S Alwarthan, N Aslam, IU Khan - IEEE Access, 2022‏ - ieeexplore.ieee.org
Nowadays, researchers from various fields have shown great interest in improving the
quality of learning in educational institutes in order to improve student achievement and …