Listar por autor UPNA "Uriz Martín, Mikel Xabier"
Mostrando ítems 1-8 de 8
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Discrete IV dG-Choquet integrals with respect to admissible orders
In this work, we introduce the notion of dG-Choquet integral, which generalizes the discrete Choquet integral replacing, in the first place, the difference between inputs represented by closed subintervals of the unit ... -
An empirical study on supervised and unsupervised fuzzy measure construction methods in highly imbalanced classification
The design of an ensemble of classifiers involves the definition of an aggregation mechanism that produces a single response obtained from the information provided by the classifiers. A specific aggregation methodology ... -
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 ... -
Mejora de los algoritmos de minería de datos: combinación de clasificadores, preprocesamiento y sus aplicaciones
El objetivo general de esta tesis es tratar de mejorar los resultados que se obtienen en los problemas de clasificación mejorando las fases que preceden y suceden a la fase de aprendizaje, es decir, a la construcción del ... -
On the influence of admissible orders in IVOVO
It is known that when dealing with interval-valued data, there exist problems associated with the non-existence of a total order. In this work we investigate a reformulation of an interval-valued decomposition strategy for ... -
On the influence of interval normalization in IVOVO fuzzy multi-class classifier
IVOVO stands for Inverval-Valued One-Vs-One and is the combination of IVTURS fuzzy classifier and the One-Vs-One strategy. This method is designed to improve the performance of IVTURS in multi-class problems, by dividing ... -
A study of different families of fusion functions for combining classifiers in the one-vs-one strategy
In this work we study the usage of different families of fusion functions for combining classifiers in a multiple classifier system of One-vs-One (OVO) classifiers. OVO is a decomposition strategy used to deal with multi-class ... -
Unsupervised fuzzy measure learning for classifier ensembles from coalitions performance
In Machine Learning an ensemble refers to the combination of several classifiers with the objective of improving the performance of every one of its counterparts. To design an ensemble two main aspects must be considered: ...