FUZZ-EQ: a data equalizer for boosting the discrimination power of fuzzy classifiers

Autor: Humberto Bustince, Mikel Elkano, Mikel Galar, Mikel Uriz

Publikováno v: Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
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The definition of linguistic terms is a critical part of the construction of any fuzzy classifier. Fuzzy partitioning methods (FPMs) range from simple uniform partitioning to sophisticated optimization algorithms. In this paper we present FUZZ-EQ, a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f717df16fa42cc496f2d3c4ad5956ab6
https://hdl.handle.net/2454/39206

Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems

Autor: Paula Fernanda Schiavo, Humberto Bustince, Graaliz Pereira Dimuro, Mikel Galar, Sidnei Pereira, Eduardo Nunes Borges, Jos Antonio Sanz, Mikel Elkano

Publikováno v: Applied Soft Computing. 67:728-740

Display Omitted A consensus method via penalty functions for decision making in ensembles of fuzzy rule-based classification systems is introduced.Overlap indices are built using overlap functions.A method for constructing confidence and support meas

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::617c0ec309d1a639cb98c097594a203e
https://doi.org/10.1016/j.asoc.2017.05.050

CC-integrals: Choquet-like Copula-based aggregation functions and its application in fuzzy rule-based classification systems

Autor: Maria Jos Asiain, Humberto Bustince, Benjamn Bedregal, Mikel Elkano, Graaliz Pereira Dimuro, Giancarlo Lucca, Jos Antonio Sanz

Publikováno v: Knowledge-Based Systems. 119:32-43

This paper introduces the concept of Choquet-like Copula-based aggregation function (CC-integral) and its application in fuzzy rule-based classification systems. The standard Choquet integral is expanded by distributing the product operation. Then, t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cfffa783f71ef4be7381010b1664aab6
https://doi.org/10.1016/j.knosys.2016.12.004

Do we still need fuzzy classifiers for Small Data in the Era of Big Data?

Autor: Mikel Galar, Mikel Elkano, Humberto Bustince

Publikováno v: FUZZ-IEEE
Academica-e: Repositorio Institucional de la Universidad Pública de Navarra
Universidad Pública de Navarra
Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname

The Era of Big Data has forced researchers to explore new distributed solutions for building fuzzy classifiers, which often introduce approximation errors or make strong assumptions to reduce computational and memory requirements. As a result, Big Da

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfbb1c807790fbeebe220858bff62b4c
https://hdl.handle.net/2454/36949

Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC)

Autor: José Antonio Sanz, Francisco Herrera, Saleh Alshomrani, Alberto Fernández, Mikel Galar, Humberto Bustince, Mikel Elkano

Publikováno v: International Journal of Approximate Reasoning. 73:108-122

Classification problems with multiple classes suppose a challenge in Data Mining tasks. There is a difficulty inherent to the learning process when trying to find the most adequate discrimination functions among the different concepts within the data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::36640e785b96c1a82cf82342480a12a2
https://doi.org/10.1016/j.ijar.2016.02.005