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...

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Detalles Bibliográficos
Autores principales: Shahrivari, Farzad, Zlatanov, Nikola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391840/
https://www.ncbi.nlm.nih.gov/pubmed/34441185
http://dx.doi.org/10.3390/e23081045

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