activity
20192021
most citedCFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems

48 citations · 48 across the 2 of their papers we have counts for

collaborators

4 papers

cs.AI2021

Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions

Tiago da Cruz Asmus, Graçaliz Pereira Dimuro, Benjamín Bedregal +3

Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. Interval-valued overlap functions were defined as an extension to exp…

cs.HC2021

Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions

Javier Fumanal-Idocin, Yu-Kai Wang, Chin-Teng Lin +3

Brain Computer Interface technologies are popular methods of communication between the human brain and external devices. One of the most popular approaches to BCI is Motor Imagery.…

cs.HC2020

Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface

Javier Fumanal-Idocin, Zdenko Takáč, Javier Fernández Jose Antonio Sanz +4

In this work we study the use of moderate deviation functions to measure similarity and dissimilarity among a set of given interval-valued data. To do so, we introduce the notion o…

cs.LG201948 cited

CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems

Mikel Elkano, Jose Sanz, Edurne Barrenechea +2

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…