Analysis on Optimal Error Exponents of Binary Classification for Source with Multiple Subclasses

We consider a binary classification problem for a test sequence to determine from which source the sequence is generated. The system classifies the test sequence based on empirically observed (training) sequences obtained from unknown sources [Formula: see text] and [Formula: see text]. We analyze t...

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Detalles Bibliográficos
Autores principales: Kuramata, Hiroto, Yagi, Hideki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141706/
https://www.ncbi.nlm.nih.gov/pubmed/35626520
http://dx.doi.org/10.3390/e24050635

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141706/
https://www.ncbi.nlm.nih.gov/pubmed/35626520
http://dx.doi.org/10.3390/e24050635

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