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Generalizing Knowledge in Decentralized Rule-Based Models

  • Pedro StrechtEmail author
  • João Mendes-Moreira
  • Carlos Soares
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 967)

Abstract

Knowledge generalization of ruled-based models, such as decision trees or decision rules, have emerged from different backgrounds. This particular kind of models, given their interpretability, offer several possibilities to be combined. Despite each distinct context, common patterns have emerged revealing the systemic nature of the problem. In this paper, we look at the problem of generalizing the knowledge contained in a set of models as a process formalizing the operations that can be addressed in alternative ways. We also include a set-up to evaluate generalized models based on their ability to replace the base ones from a predictive performance perspective, without loss of interpretability.

Keywords

Knowledge generalization Rule-based models 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.INESC TEC/Faculdade de EngenhariaUniversidade do PortoPortoPortugal

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