Using the RRT algorithm to optimize classification systems for handwritten digits and letters

Multi-objective genetic algorithms have been often used to optimize classification systems, but little is discussed on their computational cost to solve such problems. This paper optimizes a classification system with an annealing based approach, the Record-toRecord Travel algorithm. Results obtained are compared to those obtained with a multi-objective genetic algorithm in the same approach. Experiments are performed with isolated handwritten digits and uppercase letters, demonstrating both the effectiveness and lower computational cost of the annealing based approach. Keywords local search, RRT algorithm, classification systems, ensemble of classifiers

• Type: Journal
• Year: 2008
• Where: SAC
• Authors: Paulo Vinicius Wolski Radtke, Robert Sabourin, Tony Wong
• Keywords: Applied Computing, Classification Systems, Computational Cost, Multi-objective Genetic Algorithm, SAC 2008