摘要
在原有基于可扩展函数族聚类的基础上,提出了自适应可扩展函数族概念,对原来的算法CIFF和CDFF作了改进,将阈值理论与可扩展函数族相结合,设计了新的聚类算法,并对其聚类性能作了分析。实验结果表明,用自适用可扩展函数族方法进行聚类,不但使聚类在可伸缩性、增量数据处理及复杂数据类型处理等方面都表现出很好的性能,而且与原算法相比,具有聚类精度高、速度快等优点。
A conception of self-adaptive extensible function family is presented on the basis of original extensible function family-based cluster. It improves the original algorithms CIFF and CDFF. A new cluster algorithm is designed by combining threshold value theory with extensible function family and its cluster performance is analyzed. Experimental results show that the cluster made by self-adaptive extensible function family has not only excellent performances in aspects of extensibility, incremental data processing and complex data type processing, etc. , but also such merits as highly precision and fast velocity in cluster processing comparing with CIFF and CDFF.
出处
《山东科技大学学报（自然科学版）》
CAS
2007年第3期98-101,共4页
Journal of Shandong University of Science and Technology(Natural Science)
基金
国家自然科学基金项目(06063090)
关键词
函数族
可扩展函数族
自适应可扩展函数族
聚类
function family
extensible function family
self-adaptive extensible function family
cluster
