This article provides a birds-eye view on the role of decision trees in machine learning and
data science over roughly four decades. It sketches the evolution of decision tree research …

Air pollution remains as a substantial health problem, particularly regarding the combined
health risks arising from simultaneous exposure to multiple air pollutants. However …

Federated learning (FL) has garnered significant attention as a novel machine learning
technique that enables collaborative training among multiple parties without exposing raw …

European forest monitoring is a central topic nowadays due to the critical role that forests
can play in combatting climate change. Crucial information on forests is the number of tree …

Our study explores the current state of machine learning (ML) as applied to predicting and
designing organic photovoltaic (OPV) devices. We outline key considerations for selecting …

As machine learning (ML) has been widely developed in real-world applications, the privacy
of ML models draws an increasing concern. In this paper, we study how to forget specific …

Soil parameters are crucial aspects in increasing agricultural production. Even though
Bangladesh is heavily dependent on agriculture, little research has been done regarding its …

There is increasingly interest in develo** embedded machine learning hardware as it can
offer better performance in terms of privacy, bandwidth efficiency, and scalability. Gradient …

This study employs data-scra** and analysis of 11,525 Plug-in Electric Vehicle (PEV) user
reviews from 2018 to 2024, focusing on users' battery performance satisfaction with electric …

The prevalence of neurodegenerative diseases (NDDs) such as Alzheimer's (AD),
Parkinson's (PD), Essential tremor (ET), and Multiple Sclerosis (MS) is increasing alongside …