关键词: 边界度, 证据积累, 聚类边界, 分类数据

Abstract: With the wide application of categorical-attribute dataset, the demand of obtaining the cluster boundary of categorical-attribute dataset becomes more and more urgent. In order to get cluster boundaries, the individual proposed a categorical-attribute data boundary detection algorithm: CBORDER(Categorical dataset BORDER detection algorithm) In this algorithm, firstly, initializing the center of cluster by using random allocation and utilizing boundary-degree to partition clusters, at the same time, we get the evidence of capturing boundary recorders. Then, basing on the evidence accumulation, we execute the above procedure repeatedly to acquire the boundaries of clusters at the end. Multi-experimental results demonstrate that CBORDER detect boundaries of the high dimension categorical data efficiently.

Key words: boundary-degree, evidence accumulation, boundary of cluster, categorical dataset