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Fuzzy Classification Aggregation

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  • Federico Fioravanti

Abstract

We consider the problem where a set of individuals has to classify $m$ objects into $p$ categories and does so by aggregating the individual classifications. We show that if $m\geq 3$, $m\geq p\geq 2$, and classifications are fuzzy, that is, objects belong to a category to a certain degree, then an optimal and independent aggregator rule that satisfies a weak unanimity condition belongs to the family of Weighted Arithmetic Means. We also obtain characterization results for $m= p= 2$.

Suggested Citation

  • Federico Fioravanti, 2024. "Fuzzy Classification Aggregation," Papers 2402.17620, arXiv.org, revised Aug 2024.
    • Handle: RePEc:arx:papers:2402.17620
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