While methods for comparing two learning algorithms on a single data set have been
scrutinized for quite some time already, the issue of statistical tests for comparisons of more …

BACKGROUND: The widespread availability of new computational methods and tools for
data analysis and predictive modeling requires medical informatics researchers and …

Machine learning (ML) models are now routinely deployed in domains ranging from criminal
justice to healthcare. With this newfound ubiquity, ML has moved beyond academia and …

Scikit-learn is an increasingly popular machine learning li-brary. Written in Python, it is
designed to be simple and efficient, accessible to non-experts, and reusable in various …

As practitioners increasingly deploy machine learning models in critical domains such as
health care, finance, and policy, it becomes vital to ensure that domain experts function …

Permanent magnet synchronous motors (PMSMs) are widely recognized for their precise
control capabilities, making them indispensable in numerous industrial applications. Yet …

Unmanned aerial vehicles (UAVs) have gained significant importance due to their wide
applicability in modern life. Fault diagnosis plays a crucial role in ensuring their safe and …

In this paper, we explore student dropout behavior in Massive Open Online Courses
(MOOC). We use as a case study a recent Coursera class from which we develop a survival …

Widespread testing and isolation of infected patients is a cornerstone of viral outbreak
management, as underscored during the ongoing COVID-19 pandemic. Here, we report a …

Abstract Today, Artificial Intelligence is achieving prodigious real-time performance, thanks
to growing computational data and power capacities. However, there is little knowledge …