丁世飞, 史忠植, 靳奉祥, 夏士雄. 基于广义信息距离的直接聚类算法[J]. 计算机研究与发展, 2007, 44(4): 674-679.
 引用本文: 丁世飞, 史忠植, 靳奉祥, 夏士雄. 基于广义信息距离的直接聚类算法[J]. 计算机研究与发展, 2007, 44(4): 674-679.
Ding Shifei, Shi Zhongzhi, Jin Fengxiang, Xia Shixiong. A Direct Clustering Algorithm Based on Generalized Information Distance[J]. Journal of Computer Research and Development, 2007, 44(4): 674-679.
 Citation: Ding Shifei, Shi Zhongzhi, Jin Fengxiang, Xia Shixiong. A Direct Clustering Algorithm Based on Generalized Information Distance[J]. Journal of Computer Research and Development, 2007, 44(4): 674-679.

## A Direct Clustering Algorithm Based on Generalized Information Distance

• 摘要: 提出了基于广义信息距离的直接聚类算法.基于信息理论给出了离散量的基本概念，讨论并证明了离散量的一个基本不等式，进而给出了离散增量的概念.在分析距离测度的基础上，提出了广义信息距离(GID)、改进的广义信息距离(IGID)，建立了基于GID，IGID的直接聚类算法，并对土地肥力数据资料进行了聚类分析.结果表明，建立的算法与传统的聚类算法相比，算法原理简便、对数据本身的维数与分布要求不高，且具有较好的聚类效果.

Abstract: In this paper a novel direct clustering algorithm based on generalized information distance (GID) is put forward. Firstly, based on information theory, a basic concept of measure of diversity is given and an inequality about measure of diversity is proved. Based on this inequality, a concept of increment of diversity is discussed and a defined. Secondly, by analyzing distance measure, two new concepts of generalized information distance (GID) and improved generalized information distance (IGID) are proposed, and a new direct clustering algorithm based on GID and IGID is designed. Finally this algorithm is applied to soil fertility data processing, and compared with hierarchical clustering algorithm (HCA). The results of simulation application show that the algorithm presented here is feasible and effective. Because of simplicity of algorithm and robustness. It provides a new research approach for studies of pattern recognition theory.

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