Results 201 to 210 of about 5,285 (267)

An Explainable Fuzzy Framework for Assessing Preeclampsia Classification. [PDF]

Biomedicines
Salinas M, Velandia D, Mayeta-Revilla L, Bertini A, Querales M, Pardo F, Salas R.   +6 more
europepmc   +1 more source

An automated planning optimization framework for cervical intensity-modulated radiation therapy using voxel dose prediction and adaptive parameter tuning. [PDF]

Phys Imaging Radiat Oncol
Jia Q, Zhen C, Cai L, Zhu J, Wang X.
europepmc   +1 more source

Design of global climate control based on fuzzy systems with concept of carbon emissions. [PDF]

PLoS One
Naseer S, Chang WJ, Aslam MS, Hashim Bukhari M, Bilal H, Nawaz MJ.   +5 more
europepmc   +1 more source

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Meta-Fuzzy Items for Fuzzy Association Rules

2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2021
A large number of systems with a great predictive capacity, such as Deep Learning, are being currently used to solve a wide variety of real problems. However, the models obtained are not easy to understand by scientists, giving rise to the field of eXplainable Artificial Intelligence, which encourage techniques that obtain accurate and understandable ...
Carmen Biedma-Rdguez, María José Gacto, Rafael Alcalá, Jesús Alcalá-Fdez   +3 more
openaire   +1 more source

Mining fuzzy association rules

Proceedings of the sixth international conference on Information and knowledge management, 1997
In his paper, we introduce a novel technique, called F-APACS, for mining jkzy association rules. &istlng algorithms involve discretizing the domains of quantitative attrilmtes into intervals so as to discover quantitative association rules. i%ese intervals may not be concise and meaning@ enough for human experts to easily obtain nontrivial knowledge ...
Keith C. C. Chan, Wai-Ho Au
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Determination of rule weights of fuzzy association rules

10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), 2002
In this paper, first we extend two basic measures of association rules in data mining (i.e, confidence and support) to the case of fuzzy association rules. The main difference between standard and fuzzy association rules is the discretization of continuous variables.
Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima   +2 more
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On fuzzy association rules based on fuzzy cardinalities

10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), 2002
The paper discusses the benefit of using fuzzy sets in data summaries based on generalized association rules. Fuzzy sets provide a convenient interface between labels and data and allow for partial belonging to connex but distinct classes. They thus offer a robust reading of the data.
Bosc, Patrick, Dubois, Didier, Prade, Henri, Pivert, Olivier   +3 more
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On Fuzzy Confirmation Measures of Fuzzy Association Rules

2020
Many researchers from different sciences focused their attention on quantifying the degree to which an antecedent in a rule supports a conclusion. This long-standing problem results to be particularly interesting in the case of fuzzy association rules between a fuzzy antecedent and a fuzzy consequence: in fact, rules become much more flexible in ...
Celotto Emilio, Ellero Andrea, Ferretti Paola   +2 more
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