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On the normalization of interval data
(MDPI, 2020)
info:eu-repo/semantics/article,
The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on ...
Evolution in time of L-fuzzy context sequences
(Elsevier, 2016)
Artículo / Artikulua,
In this work, we consider a complete lattice L and we study L-fuzzy context sequences which
represent the evolution in time of an L-fuzzy context. To carry out this study, in the first part of
the paper, we consider n-ary ...
A proposal for tuning the α parameter in CαC-integrals for application in fuzzy rule-based classification systems
(Springer, 2020)
info:eu-repo/semantics/article,
In this paper, we consider the concept of extended Choquet integral generalized by a copula, called CC-integral. In particular, we adopt a CC-integral that uses a copula defined by a parameter α, which behavior was tested ...
Aggregation functions to combine RGB color channels in stereo matching
(Optical Society of America, 2013)
Artículo / Artikulua,
In this paper we present a comparison study between different
aggregation functions for the combination of RGB color channels in stereo
matching problem. We introduce color information from images to the
stereo matching ...
Using the Choquet integral in the fuzzy reasoning method of fuzzy rule-based classification systems
(MDPI, 2013)
Artículo / Artikulua,
In this paper we present a new fuzzy reasoning method in which the Choquet
integral is used as aggregation function. In this manner, we can take into account the
interaction among the rules of the system. For this reason, ...
Enhancing multi-class classification in FARC-HD fuzzy classifier: on the synergy between n-dimensional overlap functions and decomposition strategies
(IEEE, 2014)
Artículo / Artikulua,
There 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 compact evolutionary interval-valued fuzzy rule-based classification system for the modeling and prediction of real-world financial applications with imbalanced data
(IEEE, 2014)
Artículo / Artikulua,
The current financial crisis has stressed the need of obtaining more accurate prediction models in order to decrease the risk when investing money on economic opportunities. In addition, the transparency of the process ...
A first study on the use of interval-valued fuzzy sets with genetic tuning for classification with imbalanced data sets
(Springer, 2009)
Contribución a congreso / Biltzarrerako ekarpena,
Classification 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. ...
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 ...
General grouping functions
(Springer, 2020)
info:eu-repo/semantics/conferenceObject,
Some aggregation functions that are not necessarily associative, namely overlap and grouping functions, have called the attention of many researchers in the recent past. This is probably due to the fact that they are a ...