Construction of Pancreatic Cancer Classifier Based on SVM Optimized by Improved FOA.

A novel method is proposed to establish the pancreatic cancer classifier. Firstly, the concept of quantum and fruit fly optimal algorithm (FOA) are introduced, respectively. Then FOA is improved by quantum coding and quantum operation, and a new smell concentration determination function is defined....

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Publicado en:BioMed Research International Vol. 2015; pp. 1 - 13
Autores principales: Jiang, Huiyan, Zhao, Di, Zheng, Ruiping, Ma, Xiaoqi
Formato: Journal Article
Publicado: Wiley-Blackwell 10/12/2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 10/12/2015
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2015/781023
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          Jiang, Huiyan
          Zhao, Di
          Zheng, Ruiping
          Ma, Xiaoqi
        affil: Software College, Northeastern University, Shenyang 110819, China
      sug:
      ab: A novel method is proposed to establish the pancreatic cancer classifier. Firstly, the concept of quantum and fruit fly optimal algorithm (FOA) are introduced, respectively. Then FOA is improved by quantum coding and quantum operation, and a new smell concentration determination function is defined. Finally, the improved FOA is used to optimize the parameters of support vector machine (SVM) and the classifier is established by optimized SVM. In order to verify the effectiveness of the proposed method, SVM and other classification methods have been chosen as the comparing methods. The experimental results show that the proposed method can improve the classifier performance and cost less time.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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