In order to improve the clustering quality and efficiency of bank deposit and loan data sets, this paper has done the following work: (1) Defined the diameter of the cluster. (2) Proposed a center distance order dimensionality reduction method that uses distance scale dimensionality reduction, and proved that the new method can maintain clustering quality when reducing dimensions (this research is a complex problem). (3) Proposed an adaptive sorting clustering algorithm ASCA (Adaptive Sort Clustering Algorithm), which can effectively cluster one-dimensional data and multi-dimensional data sets. (4) Conducted detailed experiments and compared them with the traditional Cobweb algorithm and K-means algorithm. The experiments showed that the new method can reduce clustering time by up to 53%.
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