Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification

Embedding cost-sensitive factors into the classifiers increases the classification stability and reduces the classification costs for classifying high-scale, redundant, and imbalanced datasets, such as the gene expression data. In this study, we extend our previous work, that is, Dissimilar ELM (D-E...

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Detalles Bibliográficos
Autores principales: Liu, Yanqiu, Lu, Huijuan, Yan, Ke, Xia, Haixia, An, Chunlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5011754/
https://www.ncbi.nlm.nih.gov/pubmed/27642292
http://dx.doi.org/10.1155/2016/8056253

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5011754/
https://www.ncbi.nlm.nih.gov/pubmed/27642292
http://dx.doi.org/10.1155/2016/8056253

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