DOI: 10.1007/978-3-540-71629-7_27
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Multi-class Support Vector Machines Based on Arranged Decision Graphs and Particle Swarm Optimization for Model Selection

Abstract: Abstract. The use of support vector machines for multi-category problems is still an open field to research. Most of the published works use the one-against-rest strategy, but with a one-against-one approach results can be improved. To avoid testing with all the binary classifiers there are some methods like the Decision Directed Acyclic Graph based on a decision tree. In this work we propose an optimization method to improve the performance of the binary classifiers using Particle Swarm Optimization and an au… Show more

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“…Particle swarm optimization (PSO) [33] is a recent method for function minimization and it is inspired by the emergent motion of a flock of birds searching for food. This algorithm has been proposed in preliminary works by our group to tune SVMs hyperparameters [34]. Like in other SLS, the search for the optimum is an iterative process that is based on guided random decisions taken by m particles searching the space at the same time.…”
Section: Hyperparameter Optimization By Means Of Particle Swarm Optimmentioning
confidence: 99%
“…Particle swarm optimization (PSO) [33] is a recent method for function minimization and it is inspired by the emergent motion of a flock of birds searching for food. This algorithm has been proposed in preliminary works by our group to tune SVMs hyperparameters [34]. Like in other SLS, the search for the optimum is an iterative process that is based on guided random decisions taken by m particles searching the space at the same time.…”
Section: Hyperparameter Optimization By Means Of Particle Swarm Optimmentioning
confidence: 99%