A Method for Fast Feature Selection Utilizing Cross-Similarity within the Context of Fuzzy Relations
Source abstract
Abstract
Feature selection methods rooted in rough sets confront two notable limitations: their high computational complexity and sensitivity to noise, rendering them impractical for managing large-scale and noisy datasets. The primar... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Fuzzy Logic and Control Systems · Advanced Scientific Research Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (28)
Show source-provided references
1. Rough sets10.1007/BF01001956 ↗
2. Quantum and AI-based uncertainties for impact-relation map of multidimensional NFT investment decisions10.1016/j.frl.2024.105723 ↗
3. Decision-making technique with neutrosophic Z-rough set approach for sustainable industry evaluation using sine trigonometric operators10.1016/j.asoc.2024.112539 ↗
4. Evolutionary rough feature selection in gene expression data10.1109/TSMCC.2007.897498 ↗
5. Rough fuzzy sets and fuzzy rough sets10.1080/03081079008935107 ↗
6. Generalized fuzzy rough sets determined by a triangular norm10.1016/j.ins.2008.03.013 ↗
7. Real-valued hemimetric-based fuzzy rough sets and an application to contour extraction of digital surfaces10.1016/j.fss.2022.07.010 ↗
8. New uncertainty measurement for categorical data based on fuzzy information structures: an application in attribute reduction10.1016/j.ins.2021.08.089 ↗
9. Attribute reduction in decision-theoretic rough set models10.1016/j.ins.2008.05.010 ↗
10. Building a rule-based classifier—a fuzzy-rough set approach10.1109/TKDE.2009.118 ↗
11. On robust fuzzy rough set models10.1109/TFUZZ.2011.2181180 ↗
12. Two fuzzy covering rough set models and their generalizations over fuzzy lattices10.1016/j.fss.2015.05.002 ↗
13. A comprehensive study of fuzzy covering-based rough set models: definitions, properties and interrelationships10.1016/j.fss.2017.06.010 ↗
14. On some types of fuzzy covering-based rough sets10.1016/j.fss.2016.10.009 ↗
15. Attribute reduction algorithms with an anti-noise mechanism for hybrid data based on fuzzy evidence theory10.1016/j.engappai.2023.107659 ↗
16. Fuzzy soft β-covering based fuzzy rough sets and corresponding decision-making applications10.1007/s13042-018-0828-3 ↗
17. Fuzzy-rough sets assisted attribute selection10.1109/TFUZZ.2006.889761 ↗
18. Granular matrix: a new approach for granular structure reduction and redundancy evaluation10.1109/TFUZZ.2020.2984198 ↗
19. A fitting model for attribute reduction with fuzzy XX-covering10.1016/j.fss.2020.07.010 ↗
20. Discernibility measures for fuzzy β covering and their application10.1109/TCYB.2021.3054742 ↗
21. Noise-tolerant fuzzy-β-covering-based multigranulation rough sets and feature subset selection10.1109/TFUZZ.2021.3093202 ↗
22. Interactive and complementary feature selection via fuzzy multigranularity uncertainty measures10.1109/TCYB.2021.3112203 ↗
23. Multiobjective particle swarm optimization for feature selection with fuzzy cost10.1109/TCYB.2020.3015756 ↗
24. Feature selection for label distribution learning using dual-similarity based neighborhood fuzzy entropy10.1016/j.ins.2022.10.054 ↗
25. Multifuzzy β-covering approximation spaces and their information measures10.1109/TFUZZ.2022.3193448 ↗
26. Feature selection based on neighborhood discrimination index
27. UCI machine learning repository [Internet]. Irvine, CA, USA: University of California; [cited 2024 Oct 1]. Available from: http://archive.ics.uci.edu.
28. Kent Ridge bio-medical data set repository [Internet]. Granada, Spain: University of Granada; [cited 2024 Oct 1]. Available from: https://leo.ugr.es/elvira/DBCRepository.