On hyperparameter optimization of machine learning algorithms: Theory and practice
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 …
areas. To fit a machine learning model into different problems, its hyper-parameters must be …
Machine learning towards intelligent systems: applications, challenges, and opportunities
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 …
resulted in the generation of large amounts of data that can be made available for analyses …
MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …
involve many electronic control units connected through intravehicle networks (IVNs) to …
Multi-stage optimized machine learning framework for network intrusion detection
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 …
and organizations on the Internet and their concern about the security and privacy of their …
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 …
EDM is used to classify, analyze, and predict the students' academic performance, and …
Systematic literature review on machine learning and student performance prediction: Critical gaps and possible remedies
Improving the quality, developing and implementing systems that can provide advantages to
students, and predicting students' success during the term, at the end of the term, or in the …
students, and predicting students' success during the term, at the end of the term, or in the …
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 …
has led to a significant growth in Internet-of-Things (IoT) devices. The continued deployment …
An explainable model for identifying at-risk student at higher education
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 …
quality of learning in educational institutes in order to improve student achievement and …
Analysis of the factors affecting student performance using a neuro-fuzzy approach
Predicting students' academic performance and the factors that significantly influence it can
improve students' completion and graduation rates, as well as reduce attrition rates. In this …
improve students' completion and graduation rates, as well as reduce attrition rates. In this …
Feature evaluation of emerging e-learning systems using machine learning: An extensive survey
As of late, with the progression of AI and man-made brainpower, there has been a
developing spotlight on versatile e-learning. As all ways to deal with e-learning lose their …
developing spotlight on versatile e-learning. As all ways to deal with e-learning lose their …