pdf

ASCA: A Fast Adaptive Clustering Algorithm

  • 2013-09-19
  • 199.12KB
  • Points it Requires : 2

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%.

unfold

You Might Like

Uploader
mamselc
 

Recommended ContentMore

Popular Components

Just Take a LookMore

EEWorld
subscription
account

EEWorld
service
account

Automotive
development
circle

About Us Customer Service Contact Information Datasheet Sitemap LatestNews


Room 1530, 15th Floor, Building B, No.18 Zhongguancun Street, Haidian District, Beijing, Postal Code: 100190 China Telephone: 008610 8235 0740

Copyright © 2005-2024 EEWORLD.com.cn, Inc. All rights reserved 京ICP证060456号 京ICP备10001474号-1 电信业务审批[2006]字第258号函 京公网安备 11010802033920号
×