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VCI-LSTM: Vector choquet integral-based long short-term memory
(IEEE, 2022)
Artículo / Artikulua,
Choquet integral is a widely used aggregation operator on one-dimensional and interval-valued information, since it is able to take into account the possible interaction among data. However, there are many cases where the ...
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 based on the Choquet integral applied to image resizing
(Atlantis Press, 2019)
info:eu-repo/semantics/conferenceObject,
The rising volume of data and its high complexity has brought the need of developing increasingly efficient knowledge extraction techniques, which demands efficiency both in computational cost and in accuracy. Most of ...
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 ...
Learning fuzzy measures for aggregation in fuzzy rule-based models
(Springer Verlag, 2018)
info:eu-repo/semantics/conferenceObject,
Fuzzy measures are used to express background knowledge of the information sources. In fuzzy rule-based models, the rule confidence gives an important information about the final classes and their relevance. This work ...
Dissimilarity based choquet integrals
(Springer, 2020)
info:eu-repo/semantics/conferenceObject,
In this paper, in order to generalize the Choquet integral, we replace the difference between inputs in its definition by a restricted dissimilarity function and refer to the obtained function as d-Choquet integral. For ...
Enhancing LSTM for sequential image classification by modifying data aggregation
(IEEE, 2021)
Contribución a congreso / Biltzarrerako ekarpena,
Recurrent Neural Networks (RNN) model sequential information and are commonly used for the analysis of time series. The most usual operation to fuse information in RNNs is the sum. In this work, we use a RNN extended type, ...
d-Choquet integrals: Choquet integrals based on dissimilarities
(Elsevier, 2020)
info:eu-repo/semantics/article,
The paper introduces a new class of functions from [0,1]n to [0,n] called d-Choquet integrals. These functions are a generalization of the 'standard' Choquet integral obtained by replacing the difference in the definition ...
Unsupervised fuzzy measure learning for classifier ensembles from coalitions performance
(IEEE, 2020)
info:eu-repo/semantics/article,
In Machine Learning an ensemble refers to the combination of several classifiers with the objective of improving the performance of every one of its counterparts. To design an ensemble two main aspects must be considered: ...
An empirical study on supervised and unsupervised fuzzy measure construction methods in highly imbalanced classification
(IEEE, 2020)
info:eu-repo/semantics/conferenceObject,
The design of an ensemble of classifiers involves the definition of an aggregation mechanism that produces a single response obtained from the information provided by the classifiers. A specific aggregation methodology ...