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On Supervised Classification of Feature Vectors with Independent and Non-Identically Distributed Elements
In this paper, we investigate the problem of classifying feature vectors with mutually independent but non-identically distributed elements that take values from a finite alphabet set. First, we show the importance of this problem. Next, we propose a classifier and derive an analytical upper bound o...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391840/ https://www.ncbi.nlm.nih.gov/pubmed/34441185 http://dx.doi.org/10.3390/e23081045 |