A Comparative Analysis of Data Distribution Methods in an Agent-Based Neural System for Classification Tasks

  • Authors:

  • Laura Emmanuella A. Santana;Anne M. P. Canuto;Joao Carlos Xavier Junior;Andre M. C. Campos

  • Affiliations:

  • Federal University of Rio Grande do Norte (UFRN);Federal University of Rio Grande do Norte (UFRN);Federal University of Rio Grande do Norte (UFRN);Federal University of Rio Grande do Norte (UFRN)

  • Venue:
  • HIS '06 Proceedings of the Sixth International Conference on Hybrid Intelligent Systems
  • Year:
  • 2006

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Abstract

The NeurAge (Neural agents) system has been proposed as an alternative to transform the centralized decision making process of a multi-classifier system into a distributed, flexible and incremental one. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant features might be distributed over a set of agent. These applications can be classified as distributed classification tasks. In this paper, a comparative investigation of the NeurAge system using some methods for data distribution will be performed. In addition, the performance of the NeurAge system will be compared with some existing multi-classifier systems.