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Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine
This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for ca...
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| Publicat a: | Comput Math Methods Med |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Hindawi Publishing Corporation
2016
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5013239/ https://ncbi.nlm.nih.gov/pubmed/27642363 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/3572705 |
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