<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

Cluster Analysis – Data Mining Technique for Discovering Natural Groupings in the Data

Slovak University of Technology in Bratislava, Department of Mathematics, Institute of Informatics and Mathematics, Faculty of Electrical Engineering and Information Technology

Slovak University of Technology in Bratislava, Department of Mathematics and Descriptive Geometry, Faculty of Civil Engineering

Journal of Electrical Engineering

Amount of data stored in databases has been growing rapidly. With the technology of pattern recognition and statistical and mathematical techniques sieved...

Cluster Analysis – Data Mining Technique for Discovering Natural Groupings in the Data

Data publikacji: 19 kwi 2013

Zakres stron: 128 - 131

DOI: https://doi.org/10.2478/jee-2013-0019

Słowa kluczowe
data mining, clustering, K-means, self organizing maps, density based algorithm

This content is open access.

Cluster Analysis – Data Mining Technique for Discovering Natural Groupings in the Data

Data publikacji: 19 kwi 2013

Zakres stron: 128 - 131

DOI: https://doi.org/10.2478/jee-2013-0019

Słowa kluczowedata mining, clustering, K-means, self organizing maps, density based algorithm

This content is open access.

Słowa kluczowe
data mining, clustering, K-means, self organizing maps, density based algorithm