Construction of pancreatic cancer classifier based on SVM optimized by improved FOA

Jiang, H., Zhao, D., Zheng, R. and Ma, X. ORCID: 0000-0003-0074-4192, 2015. Construction of pancreatic cancer classifier based on SVM optimized by improved FOA. BioMed Research International, 2015, p. 781023. ISSN 2314-6133

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Abstract

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.

Item Type: Journal article
Publication Title: BioMed Research International
Creators: Jiang, H., Zhao, D., Zheng, R. and Ma, X.
Publisher: Hindawi Publishing Corporation
Date: 2015
Volume: 2015
ISSN: 2314-6133
Identifiers:
NumberType
10.1155/2015/781023DOI
Rights: Copyright © 2015 Huiyan Jiang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Divisions: Schools > School of Science and Technology
Depositing User: Jill Tomkinson
Date Added: 13 Apr 2016 14:54
Last Modified: 12 Oct 2017 14:58
URI: http://irep.ntu.ac.uk/id/eprint/27590

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