Listar por autor "Fernández, Alberto"
Mostrando ítems 1-6 de 6
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Enhancing multi-class classification in FARC-HD fuzzy classifier: on the synergy between n-dimensional overlap functions and decomposition strategies
Elkano Ilintxeta, Mikel ; Galar Idoate, Mikel ; Sanz Delgado, José Antonio ; Fernández, Alberto; Barrenechea Tartas, Edurne ; Herrera, Francisco; Bustince Sola, Humberto (IEEE, 2014) Artículo / ArtikuluaThere 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, ... -
A first study on the use of interval-valued fuzzy sets with genetic tuning for classification with imbalanced data sets
Sanz Delgado, José Antonio ; Fernández, Alberto; Bustince Sola, Humberto ; Herrera, Francisco (Springer, 2009) Contribución a congreso / Biltzarrerako ekarpenaClassification with imbalanced data-sets is one of the recent challenging problems in Data Mining. In this framework, the class dis- tribution is not uniform and the separability between the classes is often difficult. ... -
A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: degree of ignorance and lateral position
Sanz Delgado, José Antonio ; Fernández, Alberto; Bustince Sola, Humberto ; Herrera, Francisco (Elsevier, 2011) Artículo / ArtikuluaFuzzy Rule-Based Systems are appropriate tools to deal with classification problems due to their good properties. However, they can suffer a lack of system accuracy as a result of the uncertainty inherent in the definition ... -
IIVFDT: ignorance functions based interval-valued fuzzy decision tree with genetic tuning
Sanz Delgado, José Antonio ; Fernández, Alberto; Bustince Sola, Humberto ; Herrera, Francisco (World Scientific Publishing Company, 2012) Artículo / ArtikuluaThe choice of membership functions plays an essential role in the success of fuzzy systems. This is a complex problem due to the possible lack of knowledge when assigning punctual values as membership degrees. To face this ... -
Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning
Sanz Delgado, José Antonio ; Fernández, Alberto; Bustince Sola, Humberto ; Herrera, Francisco (Elsevier, 2010) Artículo / ArtikuluaAmong the computational intelligence techniques employed to solve classification problems, Fuzzy Rule-Based Classification Systems (FRBCSs) are a popular tool because of their interpretable models based on linguistic ... -
IVTURS: A linguistic fuzzy rule-based classification system based on a new interval-valued fuzzy reasoning method with tuning and rule selection
Sanz Delgado, José Antonio ; Fernández, Alberto; Bustince Sola, Humberto ; Herrera, Francisco (IEEE, 2013) Artículo / ArtikuluaInterval-valued fuzzy sets have been shown to be a useful tool for dealing with the ignorance related to the definition of the linguistic labels. Specifically, they have been successfully applied to solve classification ...