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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
(Elsevier, 2016)
Artículo / Artikulua,
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 ...
Improving the performance of fuzzy rule-based classification systems based on a nonaveraging generalization of CC-integrals named C-F1F2-integrals
(IEEE, 2019)
info:eu-repo/semantics/article,
A key component of fuzzy rule-based classification systems (FRBCS) is the fuzzy reasoning method (FRM) since it infers the class predicted for new examples. A crucial stage in any FRM is the way in which the information ...
A decision tree based approach with sampling techniques to predict the survival status of poly-trauma patients
(Atlantis Press, 2017)
info:eu-repo/semantics/article,
Survival prediction of poly-trauma patients measure the quality of emergency services by comparing their predictions with the real outcomes. The aim of this paper is to tackle this problem applying C4.5 since it
achieves ...
An evolutionary underbagging approach to tackle the survival prediction of trauma patients: a case study at the Hospital of Navarre
(IEEE, 2019)
info:eu-repo/semantics/article,
Survival prediction systems are used among emergency services at hospitals in order to measure their quality objectively. In order to do so, the estimated mortality rate given by a prediction model is compared with the ...
CFM-BD: a distributed rule induction algorithm for building compact fuzzy models in Big Data classification problems
(IEEE, 2020)
info:eu-repo/semantics/article,
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 ...
A fuzzy association rule-based classifier for imbalanced classification problems
(Elsevier, 2021)
Artículo / Artikulua,
Imbalanced classification problems are attracting the attention of the research community because they are prevalent in real-world problems and they impose extra difficulties for learning methods. Fuzzy rule-based ...
Motor-imagery-based brain-computer interface using signal derivation and aggregation functions
(IEEE, 2021)
info:eu-repo/semantics/article,
Brain Computer Interface (BCI) technologies are popular methods of communication between the human brain and external devices. One of the most popular approaches to
BCI is Motor Imagery (MI). In BCI applications, the ...
Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
(Elsevier, 2021)
info:eu-repo/semantics/article,
Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. They have been successfully applied as a fuzzy conjunction operation in several problems in which associativity ...
Multimodal fuzzy fusion for enhancing the motor-imagery-based brain computer interface
(IEEE, 2019)
info:eu-repo/semantics/article,
Brain–computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain and the external devices. Motor imagery–based brain–computer ...
Construction of capacities from overlap indexes
(Springer, 2017)
info:eu-repo/semantics/bookPart,
In this chapter, we show how the concepts of overlap function and overlap index can be used to define fuzzy measures which depend on the specific data of each considered problem.