Local Transition Tensor and Information Bounds for Supervised Classification Supplementary Material: Formal Derivation of the Semantic Tolerance Law
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| Natura: | Recurso digital |
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2026
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| _version_ | 1866901480610463744 |
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| author | Pérez Contreras, Benjamín Felipe |
| author_facet | Pérez Contreras, Benjamín Felipe |
| contents | <p>We define a third-order tensor Tcc′j that captures local class transition probabilities in metric spaces. Through contraction with the class prior, we obtain a scalar tolerance measure τ ∗ that provides a lower bound on mutual information via Fano’s inequality. We introduce the proxy Ψ := ˆτ · log2(K) as a computationally efficient measure of local supervised consistency.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18371265 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Local Transition Tensor and Information Bounds for Supervised Classification Supplementary Material: Formal Derivation of the Semantic Tolerance Law Pérez Contreras, Benjamín Felipe <p>We define a third-order tensor Tcc′j that captures local class transition probabilities in metric spaces. Through contraction with the class prior, we obtain a scalar tolerance measure τ ∗ that provides a lower bound on mutual information via Fano’s inequality. We introduce the proxy Ψ := ˆτ · log2(K) as a computationally efficient measure of local supervised consistency.</p> |
| title | Local Transition Tensor and Information Bounds for Supervised Classification Supplementary Material: Formal Derivation of the Semantic Tolerance Law |
| url | https://doi.org/10.5281/zenodo.18371265 |