Multigranularity Data Analysis With Zentropy Uncertainty Measure for Efficient and Robust Feature Selection
Küçük Resim Yok
Tarih
2025
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Multigranularity data analysis has recently become an active research topic in the intelligent computing and data mining fields. Feature selection via multigranularity data analysis is an effective tool for characterizing hierarchical data and enhancing the accuracy of the results. Although the multigranularity data analysis method has been widely adopted for feature selection, existing studies still present one prevalent disadvantage: multigranularity data analysis mostly focuses on information presented at a single granularity while ignoring the hierarchical structure of multigranularity data, which is contrary to the nature of multigranularity. Hence, this article proposes a multigranularity data analysis with a zentropy uncertainty measure for efficient and robust feature selection. Specifically, a consistent degree is first introduced to obtain optimal granularity combinations and establish an efficient neighborhood model for multigranularity information processing. Then, a novel and robust uncertainty measure is developed by integrating the multigranularity information, namely the zentropy-based measure. Considering its accuracy among uncertainty measures, two important measures are further designed and applied to feature selection. Extensive experiments demonstrate that the proposed method can achieve better robustness and classification performance than other state-of-the-art methods. © 2013 IEEE.
Açıklama
Anahtar Kelimeler
Feature Selection, Granular Computing, Multigranularity Data Analysis, Rough Set, Uncertainty Measure
Kaynak
IEEE Transactions on Cybernetics
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
55
Sayı
2
Künye
Yuan, K., Miao, D., Pedrycz, W., Zhang, H., & Hu, L. (2024). Multigranularity Data Analysis With Zentropy Uncertainty Measure for Efficient and Robust Feature Selection. IEEE Transactions on Cybernetics.
