EconPapers    
Economics at your fingertips  
 

Unsupervised Attribute Reduction Algorithms for Multiset-Valued Data Based on Uncertainty Measurement

Xiaoyan Guo, Yichun Peng (), Yu Li and Hai Lin ()
Additional contact information
Xiaoyan Guo: School of Computer Science, Zhuhai College of Science Technology, Zhuhai 519000, China
Yichun Peng: School of Computer Science and Engineering, Yulin Normal University, Yulin 537000, China
Yu Li: School of Alibaba Cloud Big Data Application, Zhuhai College of Science and Technology, Zhuhai 519041, China
Hai Lin: College of Mathematics and Information Science, Guangxi University, Nanning 530004, China

Mathematics, 2025, vol. 13, issue 11, 1-25

Abstract: Missing data introduce uncertainty in data mining, but existing set-valued approaches ignore frequency information. We propose unsupervised attribute reduction algorithms for multiset-valued data to address this gap. First, we define a multiset-valued information system (MSVIS) and establish θ -tolerance relation to form the information granules. Then, θ -information entropy and θ -information amount are introduced as uncertainty measures. Finally, these two UMs are used to design two unsupervised attribute reduction algorithms in an MSVIS. The experimental results demonstrate the superiority of the proposed algorithms, achieving average reductions of 50% in attribute subsets while improving clustering accuracy and outlier detection performance. Parameter analysis further validates the robustness of the framework under varying missing rates.

Keywords: rough set theory; multiset-valued data; uncertainty measurement; unsupervised attribute reduction (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/11/1718/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/11/1718/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:11:p:1718-:d:1662946

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-05-24
Handle: RePEc:gam:jmathe:v:13:y:2025:i:11:p:1718-:d:1662946