On smart Selection of Clustering Algorithms

被引：0

作者：

Li, Zhigang ^{[1
,2
]}

Li, Kunpeng ^{[2
]}

Guo, Weijia ^{[2
]}

机构：

[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China

[2] Hebei Polytech Univ, Coll Comp & Automat Control, Tangshan, Peoples R China

来源：

PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (ICCSIT 2010), VOL 8 | 2010年

关键词：

Data mining; clustering algorithms; fuzzy comprehensive evaluation; intelligence; Evaluation Index;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Currently, a large number of clustering algorithms are available for data mining. But it will be difficult for people who to a large extent know little about data mining to select an appropriate clustering algorithm. In order to solve this problem, in this paper, we first comprehensively analyze a number of clustering algorithms, then summarize their evaluation criteria and apply the so-called fuzzy comprehensive evaluation to smart comprehensive evaluation for clustering algorithm. Finally, we propose a smart choice of specific data mining algorithm to help the users who lacks the corresponding expertise.

引用

页码：49 / 52

页数：4

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