Abstract: Based on the least quadratic sum of Eulerian weight distance and the circulative iterative fuzzy clustering algorithm, a fuzzy clustering model for incomplete feature value data sets is proposed. Some clustering effects in different incomplete extent of different data sets are analyzed and demonstrated using incomplete test data sets. The model has extended the application field of fuzzy clustering algorithms

Key words: Fuzzy clustering; Incomplete data; Circulative iteration

摘要： 从加权广义欧氏权距离平方和最小概念出发，在循环迭代模糊聚类算法的基础上提出一种数据集指标值残缺的模糊聚类模型，示例分析了不同数据集在不同残缺程度下的聚类效果，拓展了模糊聚类算法应用领域。

关键词: 模糊聚类；残缺数据；循环迭代