Quantifying Redundant Information in Predicting a Target Random Variable

Entropy

Virgil Griffith¹  Tracey Ho² 

[1] School of Computing, National University of Singapore, Singapore 119077, Singapore;Computer Science and Electrical Engineering, Caltech, Pasadena, CA 91125, USA; E-Mail:

关键词: synergy;    information theory;    complex systems;    irreducibility;    synergistic information;    intersection-information;   

DOI  :  10.3390/e17074644

来源: mdpi

【 摘 要 】

We consider the problem of defining a measure of redundant information that quantifies how much common information two or more random variables specify about a target random variable. We discussed desired properties of such a measure, and propose new measures with some desirable properties.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland