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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 ...
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 ...
A survey of fingerprint classification Part II: experimental analysis and ensemble proposal
(Elsevier, 2015)
Artículo / Artikulua,
In the first part of this paper we reviewed the fingerprint classification literature from two different perspectives: the feature extraction and the classifier learning. Aiming at answering the question of which among the ...
A survey on fingerprint minutiae-based local matching for verification and identification: taxonomy and experimental evaluation
(Elsevier, 2015)
Artículo / Artikulua,
Fingerprint recognition has found a reliable application for verification or identification of people in biometrics. Globally, fingerprints can be viewed as valuable traits due to several perceptions observed by the experts; ...
IIVFDT: ignorance functions based interval-valued fuzzy decision tree with genetic tuning
(World Scientific Publishing Company, 2012)
Artículo / Artikulua,
The choice of membership functions plays an essential role in the success of fuzzy systems. This is a complex problem due to the possible lack of knowledge when assigning punctual values as membership degrees. To face this ...
A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: degree of ignorance and lateral position
(Elsevier, 2011)
Artículo / Artikulua,
Fuzzy Rule-Based Systems are appropriate tools to deal with classification problems due to their good properties. However, they can suffer a lack of system accuracy as a result of the uncertainty inherent in the definition ...
Medical diagnosis of cardiovascular diseases using an interval-valued fuzzy rule-based classification system
(Elsevier, 2013)
Artículo / Artikulua,
Objective: To develop a classifier that tackles the problem of determining the risk of a patient of suffering from a cardiovascular disease within the next ten years. The system has to provide both a diagnosis and an ...
Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning
(Elsevier, 2010)
Artículo / Artikulua,
Among the computational intelligence techniques employed to solve classification problems,
Fuzzy Rule-Based Classification Systems (FRBCSs) are a popular tool because of their
interpretable models based on linguistic ...
Positron emission tomography image segmentation based on atanassov's intuitionistic fuzzy sets
(MDPI, 2022)
Artículo / Artikulua,
In this paper, we present an approach to fully automate tumor delineation in positron emission tomography (PET) images. PET images play a major role in medicine for in vivo imaging in oncology (PET images are used to ...
Applying d-XChoquet integrals in classification problems
(IEEE, 2022)
Contribución a congreso / Biltzarrerako ekarpena,
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, ...