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...

Täydet tiedot

Tallennettuna:
Bibliografiset tiedot
Julkaisussa:Comput Math Methods Med
Päätekijät: Xi, Maolong, Sun, Jun, Liu, Li, Fan, Fangyun, Wu, Xiaojun
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Hindawi Publishing Corporation 2016
Aiheet:
Research Article
Linkit: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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