Ashwini Vaishnaw rejected the IMF’s “second group” AI tag for India, saying global studies already place the country among ...

Abstract: Electroluminescence (EL) imaging is the most widely used diagnostic technique for identifying flaws at every stage of the production, installation, and operation of solar modules. This ...

Social media and algorithmic recommendations aren’t just reflecting our divisions — they’re driving them. According to a poll conducted by Siena University and The New York Times, “most voters think ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Former athlete and Emmy-winning sports reporter Lindsay Simpson suffered a traumatic brain injury in 2018 that nearly took her life. At a recent event held by the National Academies of Sciences, ...

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 ...

Abstract: Multi-class imbalanced datasets present significant challenges in many real-world classification tasks, where certain classes are severely underrepresented. This study addresses the ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.