An analysis of data distribution in the ClassAge system: An agent-based system for classification tasks

The ClassAge (classifier 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 agents. These applications can be classified as distributed classification tasks and a method for distributing data (features or attributes) among the agents is needed. In this paper, an investigation of the impact of using data distribution among the agents in the performance of ClassAge will be performed. In this investigation, the performance of the ClassAge system will be compared with some existing multi-classifier systems. In all combination systems, a feature distribution method based on the Pearson correlation will be used.