Continuous Classification Aggregation
Fuente:
arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866908623786999808 |
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| author | Meng, Zijun |
| author_facet | Meng, Zijun |
| contents | We prove that any optimal, independent, and zero unanimous fuzzy classification aggregation function of a continuum of individual classifications of $m\ge 3$ objects into $2\le p\le m$ types must be a weighted arithmetic mean. We also provide a characterization for the case when $m=p=2$. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_05297 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Continuous Classification Aggregation Meng, Zijun Artificial Intelligence Systems and Control Theoretical Economics Combinatorics Machine Learning We prove that any optimal, independent, and zero unanimous fuzzy classification aggregation function of a continuum of individual classifications of $m\ge 3$ objects into $2\le p\le m$ types must be a weighted arithmetic mean. We also provide a characterization for the case when $m=p=2$. |
| title | Continuous Classification Aggregation |
| topic | Artificial Intelligence Systems and Control Theoretical Economics Combinatorics Machine Learning |
| url | https://arxiv.org/abs/2507.05297 |