Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Accurate prediction of mud loss volume in drilling operations is a critical challenge in industries such as petroleum engineering and geothermal well construction. Unforeseen mud loss leads to ...

There is a global imperative to end stillbirths, particularly in low middle income countries (LMICs), which suffer from disproportionate incidence. Sudden changes in fetal movement (FM) patterns often ...

The electrooxidation of glycerol offers a promising pathway for energy transition and biomass valorization, making it a key area of research. This study employs machine learning (ML) to predict the ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Powerful and practical machine learning tools for machine vision applications are already available to everyone, even if you’re not a data scientist. It might come as a bit of a surprise, but machine ...

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...

Abstract: This study explores the utilization of the Adaboost classification method, a machine learning technique, to evaluate the likelihood of individuals developing autism spectrum disorder (ASD).