Active Antinoise Fuzzy Dominance Rough Feature Selection Using Adaptive <i>K</i>-Nearest Neighbors-Reference-Cited by-同舟云学术

Active Antinoise Fuzzy Dominance Rough Feature Selection Using Adaptive K-Nearest Neighbors

Published:2023-11 Issue:11 Volume:31 Page:3944-3958
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Sang Binbin¹^ORCID,Xu Weihua²^ORCID,Chen Hongmei³^ORCID,Li Tianrui³^ORCID

Affiliation:

1. College of Computer and Information Science, Chongqing Normal University, Chongqing, China

2. College of Artificial Intelligence, Southwest University, Chongqing, China

3. School of Computing and Artificial Intelligence, Institute of Artificial Intelligence and National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China

Funder

Chongqing Normal University Foundation

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/91/10303750/10114578.pdf?arnumber=10114578

Reference59 articles.

1. Data-Distribution-Aware Fuzzy Rough Set Model and its Application to Robust Classification

2. Rough sets theory for multicriteria decision analysis

3. Fast and Robust Attribute Reduction Based on the Separability in Fuzzy Decision Systems

4. Clustering-based feature subset selection with analysis on the redundancy–complementarity dimension

5. Rough Hypercuboid Based Generalized and Robust IT2 Fuzzy C-Means Algorithm

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