Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is fou...

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Detalles Bibliográficos
Autores principales: Zhang, Yi, Ren, Jinchang, Jiang, Jianmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4455534/
https://www.ncbi.nlm.nih.gov/pubmed/26089862
http://dx.doi.org/10.1155/2015/423581

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4455534/
https://www.ncbi.nlm.nih.gov/pubmed/26089862
http://dx.doi.org/10.1155/2015/423581

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