High-dimensional data clustering for customers with duplicate attribute values

Customer analysis problem is often involved in high-dimensional data analysis. In addition, the duplicates often disrupt the cluster analysis. This paper focuses on the customer analysis of an educational organization by clustering. Eliminating duplicates is implemented to improve the clustering result.