Unsupervised space–time clustering using persistent homology
Unsupervised space–time clustering using persistent homology
Abstract This paper presents a new clustering algorithm for space–time data based on the concepts of topological data analysis and, in particular, persistent homology. Employing persistent homology—a flexible mathematical tool from algebraic topology used to extract topological information from data—in unsupervised learning is an uncommon and novel approach. A notable …