Multiclass Classification

Multiclass classification, the task of assigning data points to one of several categories, aims to develop accurate and efficient algorithms for diverse applications. Current research emphasizes robust methods handling imbalanced datasets and uncertainty, exploring architectures like support vector machines (SVMs), logistic regression, deep neural networks (including transformers), and ensemble methods, often incorporating techniques like active learning and robust optimization. These advancements are crucial for improving the reliability and interpretability of classification models across various fields, from healthcare and cybersecurity to engineering and social sciences.