Paper Info
Title
Applying d-XChoquet integrals in classification problems
Abstract
Several generalizations of the Choquet integral have been applied in the Fuzzy Reasoning Method (FRM) of Fuzzy Rule-Based Classification Systems (FRBCS’s) to improve its performance. Additionally, to achieve that goal, researchers have searched for new ways to provide more flexibility to those generalizations, by restricting the requirements of the functions being used in their constructions and relaxing the monotonicity of the integral. This is the case of CT-integrals, CC-integrals, CF-integrals, CF1F2-integrals and dCF-integrals, which obtained good performance in classification algorithms, more specifically, in the fuzzy association rule-based classification method for high-dimensional problems (FARC-HD). Thereafter, with the introduction of Choquet integrals based on restricted dissimilarity functions (RDFs) in place of the standard difference, a new generalization was made possible: the d-XChoquet (d-XC) integrals, which are ordered directional increasing functions and, depending on the adopted RDF, may also be a pre-aggregation function. Those integrals were applied in multi-criteria decision making problems and also in a motor-imagery brain computer interface framework. In the present paper, we introduce a new FRM based on the d-XC integral family, analyzing its performance by applying it to 33 different datasets from the literature.
Year
DOI
Venue
2022
10.1109/FUZZ-IEEE55066.2022.9882740
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Keywords
DocType
ISSN
d-XChoquet integral,pre-aggregation functions,OD-increasing functions,Fuzzy Rule-Based Classification System
Conference
1544-5615
ISBN
Citations 
PageRank 
978-1-6654-6711-7
0
0.34
References 
Authors
21
7
Name
Order
Citations
PageRank
Jonata C. Wieczynski101.69
Giancarlo Lucca2666.17
Eduardo Borges300.34
Leonardo Emmendorfer400.34
Mikel Ferrero-Jaurrieta500.34
Graçaliz Dimuro600.34
Humberto Bustince71938134.10