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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi Publishing Corporation
2015
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| Materias: | |
| 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 |