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Application of Imperialist Competitive Algorithm for Feature Selection: A Case Study on Bulk Rice Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 40 - Number 16 |
| Year of Publication: 2012 |
| Authors: S. J. MousaviRad, F. Akhlaghian Tab, K. Mollazade |
10.5120/5068-7485
|
S. J. MousaviRad, F. Akhlaghian Tab, K. Mollazade . Application of Imperialist Competitive Algorithm for Feature Selection: A Case Study on Bulk Rice Classification. International Journal of Computer Applications. 40, 16 ( February 2012), 41-48. DOI=10.5120/5068-7485
Abstract
Feature selection plays an important role in pattern recognition. The better selection of a feature set usually results the better performance in a classification problem. This work tries to select the best feature set for classification of rice varieties based on image of bulk samples using imperialist competition algorithm. Imperialist competition algorithm is a new evolutionary optimization method that is inspired by imperialist competition. Results showed the feature set selected by the imperialist competition algorithm provide the better classification performance compared to that obtained by genetic algorithm technique
References
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