Results 21 to 30 of about 4,802 (220)
Spherical Linear Diophantine Fuzzy Soft Rough Sets with Multi-Criteria Decision Making
Axioms, 2021 Modeling uncertainties with spherical linear Diophantine fuzzy sets (SLDFSs) is a robust approach towards engineering, information management, medicine, multi-criteria decision-making (MCDM) applications. The existing concepts of neutrosophic sets (NSs),
Masooma Raza Hashmi +4 more
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A new algorithm for feature selection based on rough sets theory
Revista Facultad de Ingeniería Universidad de Antioquia, 2014 Rough Sets Theory has opened new trends for the development of data analysis techniques. In this theory, the notion of reduct is very significant, but obtaining a reduct in a decision system is an expensive computing process although very important in ...
Yailé Caballero +4 more
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Attribute Reduction in Soft Contexts Based on Soft Sets and Its Application to Formal Contexts
Mathematics, 2020 We introduce the notion of the reduct of soft contexts, which is a special notion of a consistent set for soft contexts. Then, we study its properties and show that this notion is well explained by the two classes, 1 0 and 2 0 , of ...
Won Keun Min
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Automorphisms and Definability (of Reducts) for Upward Complete Structures
Mathematics, 2022 The Svenonius theorem establishes the correspondence between definability of relations in a countable structure and automorphism groups of these relations in extensions of the structure.
Alexei Semenov, Sergei Soprunov
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Finding Optimal Reduct for Rough Sets by Using a Decision Tree Learning Algorithm [PDF]
, 2006 Rough Set theory is a mathematical theory for classification based on structural analysis of relational data. It can be used to find the minimal reduct. Minimal reduct is the minimal knowledge representation for the relational data.
Li, Xin
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A Variable Precision Attribute Reduction Approach in Multilabel Decision Tables
The Scientific World Journal, 2014 Owing to the high dimensionality of multilabel data, feature selection in multilabel learning will be necessary in order to reduce the redundant features and improve the performance of multilabel classification.
Hua Li +4 more
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Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2015 We reduce phrase-representation parsing to dependency parsing. Our reduction is grounded on a new intermediate representation, "head-ordered dependency trees", shown to be isomorphic to constituent trees. By encoding order information in the dependency labels, we show that any off-the-shelf, trainable dependency parser can be used to produce ...
Daniel Fernández-González +1 more
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Attribute Reduction and Information Granularity [PDF]
Journal of Systemics, Cybernetics and Informatics, 2003 In the view of granularity, this paper analyzes the influence of three attribute reducts on an information system, finding that the possible reduct and m - decision reduct will make the granule view coarser, while discernible reduct will not change the ...
Li-hong Wang, Geng-feng Wu
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Reduct Driven Pattern Extraction from Clusters [PDF]
International Journal of Computational Intelligence Systems, 2009 Clustering algorithms give general description of clusters, listing number of clusters and member entities in those clusters. However, these algorithms lack in generating cluster description in the form of pattern.
Shuchita Upadhyaya +2 more
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A New Approach to Neutrosophic Hypersoft Rough Sets [PDF]
Neutrosophic Sets and Systems, 2023 The aim of this work is to introduce the new notion of Neutrosophic hypersoft rough set and study its properties. Neutrosophic hypersoft rough set is a generalization of Neutrosophic soft rough set.
V.S. Subha, R. Selvakumar
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