OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...

Service-based organizations may handle thousands of customer emails daily, placing a significant burden on IT help desks, customer service organizations, and other departments involved in reading, ...

Naïve Bayes classifiers are a cornerstone of machine learning—simple, fast, and surprisingly effective, especially for problems with large and high-dimensional data. While the underlying concept is ...

1 Department of Computer Engineering, University of Burundi (UB), Bujumbura, Burundi. 2 Ecole Normale Supérieure (ENS), Bujumbura, Burundi. 3 University Research Laboratory in Modeling and Applied ...

There is no doubt that social media sites have provided many benefits to humanity, such as sharing information continuously and communicating with others easily. It also seems that social media sites ...

The belief rule base is crucial in expert systems for intelligent diagnosis of equipment. However, in the belief rule base for fault diagnosis, multiple antecedent attributes are often initially ...

Dataset import and preprocessing Automatic feature map generation 27-type feature catalogue for iterative (re)calculation to support model integration into optimization 7 customizable internal model ...

Naive Bayes is a supervised machine learning algorithm based on Bayes' Theorem with an assumption of independence between predictors. In simple words, it calculates the probability of an event, based ...

1 College of Information Science and Technology, Jinan University, Guangzhou, China. 2 University of Birmingham Joint Institute, Jinan University, Guangzhou, China. Text classification is an essential ...

Machines today can learn in highly advanced ways. Computers churn through billions of data points to rapidly detect complex patterns and solve real-world problems. How? By using machine learning ...