Results 221 to 230 of about 185,811 (251)

Feature Selection and Classification Based on Directed Fuzzy Rough Sets

IEEE Transactions on Systems, Man & Cybernetics. Systems
Fuzzy rough sets have made considerable strides within the domain of machine learning and data mining and served as a valuable tool for feature selection. However, traditional models face challenges in computing fuzzy similarity relations.
Changyue Wang, Changzhong Wang, Shuang An, Weiping Ding, Yuhua Qian   +4 more
semanticscholar   +1 more source

A Fuzziness Measure of Rough Sets

2003
Rough set theory has been considered as a useful mean to model the vagueness and has been successfully applied in many fields. Every rough set is associated with some amount of fuzziness. In this paper, we have proposed a measure of fuzziness in rough set. Our measure prevents the inconsistency problem incurred in the measure proposed by Chakrabarty et
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Fuzzy Rough Sets

2019
In this chapter, we will discuss the Fuzzy Rough Set Theory. Some core preliminaries will be presented along with necessary details. We will also discuss some state-of-the-art fuzzy rough set approaches from the literature.
Muhammad Summair Raza, Usman Qamar
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Interval-set-valued fuzzy rough sets

Computational and Applied Mathematics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chengyong Jin, Bao Qing Hu
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A comparative study of fuzzy sets and rough sets

Information Sciences, 1998
The paper reviews and compares theories of fuzzy sets and of rough sets. Two formulations of fuzzy sets, viz., in terms of many-valued and of modal logics are considered. In both cases, the theory of fuzzy sets may be viewed as a deviation from classical set theory.
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Feature Selection Based on Weighted Fuzzy Rough Sets

IEEE transactions on fuzzy systems
Fuzzy rough set approaches have received widespread attention across the disciplines of feature selection and rule extraction. When calculating the fuzzy degree of membership of a sample within a specific class, traditional fuzzy rough sets give ...
Changzhong Wang, Changyue Wang, Yuhua Qian, Q. Leng   +3 more
semanticscholar   +1 more source

Applications of probabilistic hesitant fuzzy rough set in decision support system

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2020
Muhammad Sajjad Ali Khan, Shahzaib Ashraf, S. Abdullah, F. Ghani   +3 more
semanticscholar   +1 more source

Diversified multiple attribute group decision-making based on multigranulation soft fuzzy rough set and TODIM method

Computational and Applied Mathematics, 2020
B. Sun, Meng Zhang, Ting Wang, Xinrui Zhang   +3 more
semanticscholar   +1 more source

Differential evolution and ACO based global optimal feature selection with fuzzy rough set for cancer data classification

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2020
L. Meenachi, S. Ramakrishnan
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The entropy for rough fuzzy sets

2006 IEEE International Conference on Granular Computing, 2006
Chengyi Zhang, Bencheng Wei, Guohui Chen, Haiyan Fu   +3 more
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