电子学报2025，Vol.53Issue(2)：604-622,19.DOI:10.12263/DZXB.20240682
基于双模糊学习的鲁棒无监督特征选择算法
Robust Unsupervised Feature Selection with Double Fuzzy Learning
摘要
Abstract
Due to the curse of dimensionality,effectively discarding redundant features while retaining critical infor-mation in high-dimensional data has become a key issue.Unsupervised feature selection,which performs dimensionality reduction without any prior class information,has attracted increasing attention.However,two common issues are ignored by existing unsupervised feature selection methods:Fuzziness is a common characteristic of data,but most existing unsuper-vised feature selection methods based on regularized regression ignore this aspect,resulting in suboptimal feature subsets;Most methods fail to effectively distinguish between normal and noisy samples and are susceptible to the noise.To tackle the mentioned issues,robust unsupervised feature selection with double fuzzy(DFRFS)learning is proposed.Specifically,DFRFS learning introduces fuzzy membership into unsupervised feature selection based on regularized regression,allowing data to be shared among multiple clusters,thereby better reflecting the complex structure and uncertainty of the data.Addi-tionally,DFRFS learning assigns different weights to samples through the robust weight learning framework,thus suppress-ing the impact of noise while retaining the effect of normal samples.Experiments on toy and real-world datasets have dem-onstrated the effectiveness of the proposed method DFRFS learning.关键词
无监督学习/特征选择/模糊学习/稀疏学习/维数约简Key words
unsupervised learning/feature selection/fuzzy learning/sparse learning/dimensionality reduction分类
计算机与自动化引用本文复制引用
高云龙,史曙光,赵志翔,曹超,潘金艳..基于双模糊学习的鲁棒无监督特征选择算法[J].电子学报,2025,53(2):604-622,19.基金项目
国家自然科学基金(No.42076058) （No.42076058）
福建省促进海洋与渔业产业高质量发展专项资金(No.FJHYF-ZH-2023-05) （No.FJHYF-ZH-2023-05）
福建省自然科学基金(No.2020J01713,No.2022J01061) （No.2020J01713,No.2022J01061）
广东省基础与应用基础研究基金(No.2024A1515011682) National Natural Science Foundation of China(No.42076058) （No.2024A1515011682）
Special Foundation of Fujian Province to Promote High-quality Development of Marine and Fishery Industries(No.FJHYF-ZH-2023-05) （No.FJHYF-ZH-2023-05）
The Natural Science Foundation of Fujian Province of China(No.2020J01713,No.2022J01061) （No.2020J01713,No.2022J01061）
The Guangdong Basic and Applied Basic Research Foundation(No.2024A1515011682) （No.2024A1515011682）
