TDApplied: An R package for machine learning and inference with persistence diagrams

Abstract

Topological data analysis is a collection of tools, based on the mathematical fields of topology and geometry, for finding structure in whole datasets. Its main tool, persistent homology (Edelsbrunner et al., 2000; Zomorodian & Carlsson, 2005), computes a shape descriptor of a dataset called a persistence diagram which encodes information about holes that exist in the dataset (example applications span a variety of areas, see for example Gracia-Tabuenca et al. (2020), Haim Meirom & Bobrowski (2022)