On the scaled Rényi entropy and application
Pengyue Yu and
Yong Deng
Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 1, 84-97
Abstract:
Rényi entropy has been widely used in many applications. However, the significance of the parameter α in Rényi entropy and how to determine the value of α is still an open issue. To explore the significance of α, a scaled Rényi entropy is proposed in this article, where α is a scaled constant. Based on the information dimension of mass function in a power set whose uncertainty is measured by Deng entropy, the scale of α in Rényi entropy of the probability distribution is determined. One numerical example is given to show its properties. The scaled Rényi entropy and Rényi entropy are then applied to the C 4.5 decision tree and active learning to compare the usefulness of scaled Rényi and Rényi entropy.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2024.2301986 (text/html)
Access to full text is restricted to subscribers.
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:taf:lstaxx:v:54:y:2025:i:1:p:84-97
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2024.2301986
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().