Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...

A multi-class classification problem is one where the goal is to predict a discrete variable that has three or more possible values. For example, you might want to predict a person's political leaning ...

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified blueprint for researchers to navigate classification, clustering, ...

Multi-label classification is a dynamic field within machine learning that allows a single instance to be associated with multiple labels simultaneously. Over recent years, advances in this domain ...