• Aleta C. Fabregas Graduate Programs, Technological Institute of the Philippines,Quezon City, Philippines
  • Bobby D. Gerardo Institute of Information and Communication Technology, West Visayas State University, Lapaz, Iloilo City, Philippines
  • Bartolome T. Tanguilig III Graduate Programs, Technological Institute of the Philippines, Quezon City, Philippines



K-means Algorithm, Euclidian Distance, Centroids, Clustering, Modified-K-means Algorithm Weighted Average Mean


This study focuses on the improved initialization of initial centroids instead of random selection for the K-means algorithm. The random selection of initial seeds is a major drawback of the original Kmeans algorithm because it leads to less reliable result of clustering the data. The modified approach of the k-means algorithm integrates the computation of the weighted mean to improve the seeds initialization. This paper shows the comparison of K-Means and Modified K-Means algorithm, using the first simple dataset of four objects and the dataset for service vehicles. The two simple applications proved that the Modified K- Means of selecting initial centroids is more reliable than K-Means Algorithm. Clustering is better achieved in the modified k-means algorithm.


A Tutorial on Clustering Algorithms, Retrieved from Intranet,

Khedr A. E., Seddawy, A., &Idrees A... (2014) “Performance Tuning of K-Mean ClusteringAlgorithm a Step towards Efficient DSS” International Journal of Innovative Research inComputer Science & Technology (IJIRCST), ISSN: 2347-5552, Volume 2, Issue 6

Kushwah S. P. S,.Rawat K, Gupta P., (2012) ”Analysis and Comparison of Efficient Techniques of Clustering Algorithms in Data Mining” International Journal of Innovative Technology andExploring Engineering (IJITEE) ISSN: 2278-3075,Volume-1, Issue-3

K-means Clustering algorithm- Data Clustering Algorithms ( clustering-algorithmk-means) K-means clustering From Wikipedia, the free encyclopedia

Oyelade, O. J, Oladipupo, O. O, Obagbuwa, I. C, (2010) “Application of k-Means Clustering algorithm for prediction of Students’ Academic Performance” International Journal of Computer Science and Information Security (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, _o. 1, 2010 Teknomo, K. PhD, Teknomo, K-Means Clustering Tutorial K-Means Clustering Tutorials. (2007)(http:people.revoledu.comkardi tutorialkMeanWeighted_average (




How to Cite

Fabregas, A., Gerardo, B., & Tanguilig III, B. (2016). MODIFIED SELECTION OF INITIAL CENTROIDS FOR K- MEANS ALGORITHM. MATTER: International Journal of Science and Technology, 2(2), 48–64.