English(EN) Optimal aggregation in multiclass classification

新研究探讨多类分类的最优聚合

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-21 04:00

本文探讨了多类分类问题的最优聚合技术，将现有方法从二元分类扩展而来。它引入了新颖的聚合框架，实现了最优或接近最优的收敛速率，尤其独立于类别的数量。该研究强调了传统proper aggregation的局限性，并提出了improper probability-mixture aggregates来克服这些挑战。 AI

排序理由该条目是一篇在arXiv上发表的学术论文，详细介绍了统计学和机器学习的新研究。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv stat.ML TIER_1 English(EN) · Felix Abramovich, Or Davidovitch-Servadio · 2026-10-21 04:00

Optimal aggregation in multiclass classification

arXiv:2610.28025v1 Announce Type: cross Abstract: This paper studies the problem of aggregation in multiclass classification, generalizing existing results for binary classification. Given a finite dictionary of score functions F={f_1,...,f_M} and a training sample, the goal is t…

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Optimal aggregation in multiclass classification

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