Tsallis Mutual Information for Document Classification

Entropy

Màrius Vila¹  Anton Bardera²  Miquel Feixas² 

[1] Institut d’Informàtica i Aplicacions, Universitat de Girona, Campus Montilvi, Girona 17071, Spain;

关键词: Tsallis entropy;    mutual information;    image similarity;    document classification;   

DOI  :  10.3390/e13091694

来源: mdpi

【 摘 要 】

Mutual information is one of the mostly used measures for evaluating image similarity. In this paper, we investigate the application of three different Tsallis-based generalizations of mutual information to analyze the similarity between scanned documents. These three generalizations derive from the Kullback–Leibler distance, the difference between entropy and conditional entropy, and the Jensen–Tsallis divergence, respectively. In addition, the ratio between these measures and the Tsallis joint entropy is analyzed. The performance of all these measures is studied for different entropic indexes in the context of document classification and registration.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.