Consistency and Generalization Bounds for Maximum Entropy Density Estimation

Entropy

Shaojun Wang²  Russell Greiner¹ 

[1] Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada; E-Mail:;Kno.e.sis Center, Department of Computer Science and Engineering, Wright State University, Dayton, OH 45435, USA

关键词: maximum entropy principle;    density estimation;    generalization bound;    consistency;   

DOI  :  10.3390/e15125439

来源: mdpi

【 摘 要 】

We investigate the statistical properties of maximum entropy density estimation, both for the complete data case and the incomplete data case. We show that under certain assumptions, the generalization error can be bounded in terms of the complexity of the underlying feature functions. This allows us to establish the universal consistency of maximum entropy density estimation.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.