Systematic Feature Selection Based on Three-Level Improvements of Fuzzy Dominance Three-Way Neighborhood Rough Sets
Author:
Affiliation:
1. School of Mathematical Sciences, Sichuan Normal University, Chengdu, China
2. Department of Computer Science and Technology, Tongji University, Shanghai, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Sichuan Province of China
Sichuan Science and Technology Program of China
Humanities and Social Sciences Project of the Ministry of Education of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/91/10665743/10621649.pdf?arnumber=10621649
Reference37 articles.
1. A novel approach for learning label correlation with application to feature selection of multi-label data
2. Unsupervised Feature Selection With Weighted and Projected Adaptive Neighbors
3. A survey on swarm intelligence approaches to feature selection in data mining
4. Maximum Correntropy Criterion-Based Sparse Subspace Learning for Unsupervised Feature Selection
5. Improved evolutionary-based feature selection technique using extension of knowledge based on the rough approximations
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