Listar por autor UPNA "Elkano Ilintxeta, Mikel"
Mostrando ítems 1-7 de 7
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An algorithm for group decision making using n -dimensional fuzzy sets, admissible orders and OWA operators
In this paper we propose an algorithm to solve group decision making problems using n -dimensional fuzzy sets, namely, sets in which the membership degree of each element to the set is given by an in- creasing tuple of n ... -
CFM-BD: a distributed rule induction algorithm for building compact fuzzy models in Big Data classification problems
Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions and decisions. However, when it comes to ... -
Do we still need fuzzy classifiers for small data in the era of big data?
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 ... -
Enhancing multi-class classification in FARC-HD fuzzy classifier: on the synergy between n-dimensional overlap functions and decomposition strategies
There are many real-world classification problems involving multiple classes, e.g., in bioinformatics, computer vision or medicine. These problems are generally more difficult than their binary counterparts. In this scenario, ... -
FUZZ-EQ: a data equalizer for boosting the discrimination power of fuzzy classifiers
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 ... -
Fuzzy rule-based classification systems for multi-class problems using binary decomposition strategies: on the influence of n-dimensional overlap functions in the fuzzy reasoning method
Multi-class classification problems appear in a broad variety of real-world problems, e.g., medicine, genomics, bioinformatics, or computer vision. In this context, decomposition strategies are useful to increase the ... -
Novel methodologies for improving fuzzy classifiers: dealing with multi-class and Big Data classification problems
Los Sistemas de Clasificación Basados en Reglas Difusas (SCBRDs) son métodos de aprendizaje automático que permiten construir modelos predictivos capaces de predecir la clase a la que pertenecen los datos de entrada. La ...