Multi-Granulation Entropy and Its Applications

作者：Zeng, Kai^*; She, Kun; Niu, Xinzheng

来源：Entropy, 2013, 15(6): 2288-2302.

DOI：10.3390/e15062288

• multi-granulation
• entropy
• feature selection

In the view of granular computing, some general uncertainty measures are proposed through single-granulation by generalizing Shannon's entropy. However, in the practical environment we need to describe concurrently a target concept through multiple binary relations. In this paper, we extend the classical information entropy model to a multi-granulation entropy model (MGE) by using a series of general binary relations. Two types of MGE are discussed. Moreover, a number of theorems are obtained. It can be concluded that the single-granulation entropy is the special instance of MGE. We employ the proposed model to evaluate the significance of the attributes for classification. A forward greedy search algorithm for feature selection is constructed. The experimental results show that the proposed method presents an effective solution for feature analysis.

• 出版日期2013-6
• 单位电子科技大学