Abstract
this paper describes the universal analyst: Eureka-Universe, a framework for Business Analytics and Business Intelligence based on compensatory fuzzy logic (CFL), which solves problems that handle vague, incomplete or, inaccurate information. Eureka-Universe facilitates knowledge discovery (KD), knowledge engineering and, decision analysis and modeling. The architecture of Eureka-Universe mainly includes a project manager, a scientific core, and algebraic and graphical editors for developing KD tasks. The project manager allows to create or modify models of a problem. The scientific core performs the KD tasks through an evolutionary algorithm. The text editor executes KD tasks, and the graphical editor displays and modifies FPs seen as fuzzy trees. Eureka-Universe can perform inference tasks by combining the discovery and evaluation tasks; furthermore, it offers interpretability possibilities by analyzing the FPs seen as fuzzy trees in the graphical editor. The Eureka-Universe architecture is described and validated by realistic study cases. Finally, the paper envisions new features to develop as future work for this framework.
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Padrón-Tristán, J.F. et al. (2022). Eureka-Universe: A Business Analytics and Business Intelligence System. In: Castillo, O., Melin, P. (eds) New Perspectives on Hybrid Intelligent System Design based on Fuzzy Logic, Neural Networks and Metaheuristics. Studies in Computational Intelligence, vol 1050. Springer, Cham. https://doi.org/10.1007/978-3-031-08266-5_26
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