An Improved Kernel Credal Classification Algorithm Based on Regularized Mahalanobis Distance: Application to Microarray Data Analysis

Within the kernel methods, an improved kernel credal classification algorithm (KCCR) has been proposed. The KCCR algorithm uses the Euclidean distance in the kernel function. In this article, we propose to replace the Euclidean distance in the kernel with a regularized Mahalanobis metric. The Mahala...

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Detalles Bibliográficos
Autores principales: EL bendadi, Khawla, Lakhdar, Yissam, Sbai, El Hassan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040306/
https://www.ncbi.nlm.nih.gov/pubmed/30050567
http://dx.doi.org/10.1155/2018/7525786

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040306/
https://www.ncbi.nlm.nih.gov/pubmed/30050567
http://dx.doi.org/10.1155/2018/7525786

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