Uyghur Text Feature Selection Methods by Artificial Fish Optimization
Journal Title: 河南科技大学学报（自然科学版） - Year 2016, Vol 37, Issue 6
Abstract
Feature selection was a key step in text classification,which had direct effect on the classification results. The basic principles of artificial fish behaviors of foraging,gregarious and rear-end were analyzed.Combined with the principle of Uyghur text feature extraction,a kind of improved artificial fish swarm algorithm to Uyghur text feature extraction was proposed. In order to speed up the convergence rate of fish,a strategy was taken into fish behaviors by changing the perspective. At the same time,the mutation strategy was added to the algorithm to avoid falling into local optimal solution. Finally,the sample after feature selection was input into the classifiers to perform the simulation experiment. The results show that the improved artificial fish swarm algorithm can make the classification accuracy reach 94.5%.
Authors and Affiliations
Bingbing WU, •Abudureyimu HALIDAN, •Aierken ALIYA, Yan HE
Keywords
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- EP ID EP477490
- DOI 10.15926/j.cnki.issn1672-6871.2016.06.010
- Views 93
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