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

CANUTO, A.M.P., SANTANA, L.E.A., ABREU, Marjory C.C. and XAVIER, J.C. (2008). An analysis of data distribution in the ClassAge system: An agent-based system for classification tasks. Neurocomputing, 71 (16-18), 3319-3325.

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Official URL: https://www.sciencedirect.com/science/article/pii/...
Link to published version:: https://doi.org/10.1016/j.neucom.2008.01.032
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    Abstract

    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. © 2008 Elsevier B.V. All rights reserved.

    Item Type: Article
    Uncontrolled Keywords: Multi-agent systems; Data distribution methods (or feature selection methods); Multi-classifier systems; Pattern recognition; 08 Information and Computing Sciences; 09 Engineering; 17 Psychology and Cognitive Sciences; Artificial Intelligence & Image Processing
    Identification Number: https://doi.org/10.1016/j.neucom.2008.01.032
    Page Range: 3319-3325
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 06 Aug 2020 11:19
    Last Modified: 06 Aug 2020 11:19
    URI: http://shura.shu.ac.uk/id/eprint/25390

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