Persistence kernels for classification: A comparative study
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866909286480740352 |
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| author | Bandiziol, Cinzia De Marchi, Stefano |
| author_facet | Bandiziol, Cinzia De Marchi, Stefano |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_07090 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Persistence kernels for classification: A comparative study Bandiziol, Cinzia De Marchi, Stefano Machine Learning Algebraic Topology 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. |
| title | Persistence kernels for classification: A comparative study |
| topic | Machine Learning Algebraic Topology |
| url | https://arxiv.org/abs/2408.07090 |