A comparative study of different machine learning methods on microarray gene expression data

BACKGROUND: Several classification and feature selection methods have been studied for the identification of differentially expressed genes in microarray data. Classification methods such as SVM, RBF Neural Nets, MLP Neural Nets, Bayesian, Decision Tree and Random Forrest methods have been used in r...

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Detalles Bibliográficos
Autores principales: Pirooznia, Mehdi, Yang, Jack Y, Yang, Mary Qu, Deng, Youping
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386055/
https://www.ncbi.nlm.nih.gov/pubmed/18366602
http://dx.doi.org/10.1186/1471-2164-9-S1-S13

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2386055/
https://www.ncbi.nlm.nih.gov/pubmed/18366602
http://dx.doi.org/10.1186/1471-2164-9-S1-S13

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