A Novel Unsupervised Feature Selection for High-Dimensional Data Based on FCM and k-Nearest Neighbor Rough Sets.
- DOI
- 10.1109/tnnls.2024.3460796
- Published
- 2025 Jun
- Container
- IEEE transactions on neural networks and learning systems
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2024.3460796,
title = {A Novel Unsupervised Feature Selection for High-Dimensional Data Based on FCM and k-Nearest Neighbor Rough Sets.},
author = {Xu W and Zhang Y and Qian Y},
year = {2025},
journal = {IEEE transactions on neural networks and learning systems},
doi = {10.1109/tnnls.2024.3460796},
url = {https://doi.org/10.1109/tnnls.2024.3460796}
}RIS
TY - JOUR TI - A Novel Unsupervised Feature Selection for High-Dimensional Data Based on FCM and k-Nearest Neighbor Rough Sets. AU - Xu W AU - Zhang Y AU - Qian Y PY - 2025 JO - IEEE transactions on neural networks and learning systems DO - 10.1109/tnnls.2024.3460796 UR - https://doi.org/10.1109/tnnls.2024.3460796 ER -
APA
W, X., Y, Z., & Y, Q. (2025). A Novel Unsupervised Feature Selection for High-Dimensional Data Based on FCM and k-Nearest Neighbor Rough Sets.. IEEE transactions on neural networks and learning systems. https://doi.org/10.1109/tnnls.2024.3460796
Source records
- pubmed · retrieved 2026-09-25T13:27:08.114Z