FARM: A New Efficient and Effective Data Clustering Algorithm

被引:0
|
作者
Tsai, Cheng-Fa [1 ]
Lee, Kuei-Sheng [1 ]
机构
[1] Natl Pingtung Univ Sci & Technol, Dept Management Informat Syst, Pingtung, Taiwan
关键词
data mining; data clustering; database; density-based clustering; grid-based clustering; algorithm;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This investigation presents a method named FARM that combines a grid-based algorithm with the density-based approach for clustering data in data mining applications. In the FARM clustering method, the number of separate clusters need not be specified but only the number of divisions of the clusters is required. Experimental results indicate that the proposed method clusters correctly. It filters 98.8% of the noise, and the data set accuracy exceeds 99.7%. The most surprising result is the time required to process data sets. Processing 575,000 data sets takes only 0.33 second - much less time than any currently known clustering algorithm.
引用
收藏
页码:253 / +
页数:2
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