Incremental continuous ant colony optimization technique for support vector machine model selection problem
Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem. In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a n...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/6967/1/P12_-_AMATHI_2012.pdf |
| Summary: | Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem. In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time. This study proposes an algorithm that can optimize Support Vector Machine parameters using Incremental Continuous Ant Colony
Optimization without the need to discretize continuous value for support vector machine parameters.Seven datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithmin terms of classification accuracy.Promising results were obtained when compared to grid search technique. |
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