CLUSTER ANALYSIS - DATA MINING TECHNIQUE FOR DISCOVERING NATURAL GROUPINGS IN THE DATA

被引：2

作者：

Pastuchova, Elena ^{[1
]}

Vaclavikova, Stefania ^{[2
]}

机构：

[1] Slovak Univ Technol Bratislava, Dept Math, Inst Informat & Math, Fac Elect Engn & Informat Technol, Bratislava, Slovakia

[2] Slovak Univ Technol Bratislava, Dept Math & Descript Geometry, Fac Civil Engn, Bratislava, Slovakia

来源：

JOURNAL OF ELECTRICAL ENGINEERING-ELEKTROTECHNICKY CASOPIS | 2013年 / 64卷 / 02期

关键词：

data mining; clustering; K-means; self organizing maps; density based algorithm;

D O I：

10.2478/jee-2013-0019

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Amount of data stored in databases has been growing rapidly. With the technology of pattern recognition and statistical and mathematical techniques sieved across the stored information, data mining helps researchers recognize important facts, relationships, trends, patterns, derogations and anomalies that might otherwise go undetected. One of the major data mining techniques is clustering In this paper some of clustering methods, helpful in many applications, are compared. We assess the suitability of the software that we used for clustering.

引用

页码：128 / 131

页数：4

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