Alexandre Leblanc

Automatic depth-based local center clustering via $\beta$-integrated local depth and adaptive grouping

Clustering is an unsupervised learning technique that partitions unlabeled data into groups. Most existing methods require user-specified parameters, such as the number of clusters or neighborhood size. Conversely, we propose automatic depth-based local center clustering (A-DLCC), a fully data-driven method that elimin...