![](/images/graphics-bg.png)
An efficient algorithm for initializing centroids in K-means clustering
Joint Authors
Ulaywi, Ahmad Husayn
Janabi, Kazim B. S.
Source
Journal of Kufa for Mathematics and Computer
Issue
Vol. 3, Issue 2 (31 Dec. 2016), pp.18-24, 7 p.
Publisher
University of Kufa Faculty of Mathematics and Computers Science
Publication Date
2016-12-31
Country of Publication
Iraq
No. of Pages
7
Main Subjects
Abstract EN
Clustering represents one of the most popular knowledge extraction algorithms in data mining techniques.
Hierarchical and partitioning approaches are widely used in this field.
Each has its own advantages, drawbacks and goals.
K-means represents the most popular partitioning clustering technique, however it suffers from two major drawbacks; time complexity and its sensitivity to the initial centroid values.
The work in this paper presents an approach for estimating the starting initial centroids throughout three process including density based, normalization and smoothing ideas.
The proposed algorithm has a strong mathematical foundation.
The proposed approach was tested using a free standard data (20000 records).
The results showed that the approach has better complexity and ensures the clustering convergence.
American Psychological Association (APA)
Ulaywi, Ahmad Husayn& Janabi, Kazim B. S.. 2016. An efficient algorithm for initializing centroids in K-means clustering. Journal of Kufa for Mathematics and Computer،Vol. 3, no. 2, pp.18-24.
https://search.emarefa.net/detail/BIM-770976
Modern Language Association (MLA)
Ulaywi, Ahmad Husayn& Janabi, Kazim B. S.. An efficient algorithm for initializing centroids in K-means clustering. Journal of Kufa for Mathematics and Computer Vol. 3, no. 2 (Dec. 2016), pp.18-24.
https://search.emarefa.net/detail/BIM-770976
American Medical Association (AMA)
Ulaywi, Ahmad Husayn& Janabi, Kazim B. S.. An efficient algorithm for initializing centroids in K-means clustering. Journal of Kufa for Mathematics and Computer. 2016. Vol. 3, no. 2, pp.18-24.
https://search.emarefa.net/detail/BIM-770976
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 23-24
Record ID
BIM-770976