关键词: 层次聚类, 信息增益, 属性加权

Abstract: Hierarchical clustering analysis is a very important subject in the fields of pattern recognition and data mining, and has a broad application prospect. Inspired by the idea of selecting the best classification attributes in decision tree algorithm, a novel hierarchical clustering algorithm using information gain is proposed. This algorithm directs the attribute weighting in a hierarchical clustering by computing the information gains, thereby improving the quality of clustering results. The experiment results on UCI machine learning data sets indicate that it yields better stability compared with the quondam hierarchical clustering algorithm.

Key words: hierarchical clustering, information gain, attribute weighting