Artículo
A Survey of Vectorization Methods in Topological Data Analysis
Autor/es | Ali, Dashti
Asaad, Aras Jiménez Rodríguez, María José ![]() ![]() ![]() ![]() ![]() ![]() ![]() Nanda, Vidit Paluzo Hidalgo, Eduardo Soriano Trigueros, Manuel |
Departamento | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Fecha de publicación | 2023-12 |
Fecha de depósito | 2024-02-08 |
Publicado en |
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Resumen | Attempts to incorporate topological information in supervised learning tasks have resulted in the creation of several techniques for vectorizing persistent homology barcodes. In this paper, we study thirteen such methods. ... Attempts to incorporate topological information in supervised learning tasks have resulted in the creation of several techniques for vectorizing persistent homology barcodes. In this paper, we study thirteen such methods. Besides describing an organizational framework for these methods, we comprehensively benchmark them against three well-known classification tasks. Surprisingly, we discover that the best-performing method is a simple vectorization, which consists only of a few elementary summary statistics. Finally, we provide a convenient web application which has been designed to facilitate exploration and experimentation with various vectorization methods. |
Cita | Ali, D., Asaad, A., Jiménez Rodríguez, M.J., Nanda, V., Paluzo Hidalgo, E. y Soriano Trigueros, M. (2023). A Survey of Vectorization Methods in Topological Data Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (12), 14069-14080. https://doi.org/10.1109/TPAMI.2023.3308391. |
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