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Fast Efficient Clustering Algorithm for Balanced Data

مؤلف البحث
Adel A. Sewisy , M. H. Marghny , Rasha M. Abd ElAziz , Ahmed I. Taloba
مجلة البحث
International Journal of Advanced Computer Science & Applications
المشارك في البحث
تصنيف البحث
1
عدد البحث
Vol. 5 - No. 6
موقع البحث
http://thesai.org/Publications/ViewPaper?Volume=5&Issue=6&Code=IJACSA&SerialNo=19
سنة البحث
2014
صفحات البحث
pp 123-129
ملخص البحث

The Cluster analysis is a major technique for statistical analysis, machine learning, pattern recognition, data mining, image analysis and bioinformatics. K-means algorithm is one of the most important clustering algorithms. However, the k-means algorithm needs a large amount of computational time for handling large data sets. In this paper, we developed more efficient clustering algorithm to overcome this deficiency named Fast Balanced k-means (FBK-means). This algorithm is not only yields the best clustering results as in the k-means algorithm but also requires less computational time. The algorithm is working well in the case of balanced data.