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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2410.11579 |
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| _version_ | 1866913547543379968 |
|---|---|
| author | Polkowski, Lech T. |
| author_facet | Polkowski, Lech T. |
| contents | Rough sets (RS)proved a thriving realm with successes inn many fields of ML and AI. In this note, we expand RS to RM - rough mereology which provides a measurable degree of uncertainty to those areas. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_11579 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Machine Learning via rough mereology Polkowski, Lech T. Machine Learning Rough sets (RS)proved a thriving realm with successes inn many fields of ML and AI. In this note, we expand RS to RM - rough mereology which provides a measurable degree of uncertainty to those areas. |
| title | Machine Learning via rough mereology |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2410.11579 |