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....
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 |
Similar Items
-
A Novel Multiinstance Learning Approach for Liver Cancer Recognition on Abdominal CT Images Based on CPSO-SVM and IO
by: Huiyan Jiang, et al.
Published: (2013-01-01) -
LGMS-FOA: An Improved Fruit Fly Optimization Algorithm for Solving Optimization Problems
by: Dan Shan, et al.
Published: (2013-01-01) -
Construction of Classifier Based on MPCA and QSA and Its Application on Classification of Pancreatic Diseases
by: Huiyan Jiang, et al.
Published: (2013-01-01) -
A SAR Image Classification Algorithm Based on Multi-Feature Polarimetric Parameters Using FOA and LS-SVM
by: Shiyu Luo, et al.
Published: (2019-01-01) -
SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier
by: Mei-Ling Huang, et al.
Published: (2014-01-01)