Rule weight specification in fuzzy rule-based classification systems

By Hisao Ishibuchi, Takashi Yamamoto. IEEE transactions on fuzzy systems, 2005

499 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/f51868c85a14f73d60d60411043dff8491152ac9

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In Artificial Intelligence

In Computational Theory and Mathematics

Citations in the corpus

Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics (2012, methodology): “…been proposed, although we have considered as a good choice the use of the heuristic method known as the Penalized Certainty Factor (PCF) Ishibuchi and Yamamoto (2005): PCFj ¼ P xp2CjlAj ðxpÞ P xpRCj lAj ðxpÞPm p¼1lAj ðxpÞ ð10Þ where xp is the pth example of the training set, Cj is the…”
A Fuzzy Association Rule-Based Classification Model for High-Dimensional Problems With Genetic Rule Selection and Lateral Tuning (2011, methodology): “In [45], we can find some heuristic methods for rule weight specification.”
Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning (2007, methodology): “Several methods were examined to determine the rule weight of each fuzzy rule in [27] where good results were obtained from the following specification:”
FURIA: an algorithm for unordered fuzzy rule induction (2009, methodology): “Despite the existence of many sound algorithms for rule induction, the field still enjoys great popularity and, as shown by recent publications (Ishibuchi and Yamamoto, 2005; Cloete and Van Zyl, 2006; Juang et al., 2007; Fernández et al., 2007), offers scope for further improvements.”
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets (2008, methodology): “In [26] another heuristic method for rule weight specification is proposed, called the P-CF:”