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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Bibliographic Details
Main Authors: Huiyan Jiang, Di Zhao, Ruiping Zheng, Xiaoqi Ma
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:BioMed Research International
Online Access:http://dx.doi.org/10.1155/2015/781023
Description
Summary: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.
ISSN:2314-6133
2314-6141