Persistence Symmetric Kernels for Classification: A Comparative Study

Autor: Cinzia Bandiziol, Stefano De Marchi
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Symmetry, Vol 16, Iss 9, p 1236 (2024)
Druh dokumentu: article
ISSN: 2073-8994
DOI: 10.3390/sym16091236
Popis: The aim of the present work is a comparative study of different persistence kernels applied to various classification problems. After some necessary preliminaries on homology and persistence diagrams, we introduce five different kernels that are then used to compare their performances of classification on various datasets. We also provide the Python codes for the reproducibility of results and, thanks to the symmetry of kernels, we can reduce the computational costs of the Gram matrices.
Databáze: Directory of Open Access Journals
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