@Article{JICS-9-4,
author = {},
title = {Enhanced K-Means Clustering Algorithm using A Heuristic Approach},
journal = {Journal of Information and Computing Science},
year = {2014},
volume = {9},
number = {4},
pages = {277--284},
abstract = {K-means algorithm is one of the most popular clustering algorithms that has been survived for 
more than 4 decades. Despite its inherent flaw of not knowing the number of clusters in advance, very few 
methods have been proposed in the literature to overcome it. The paper contains a fast heuristic algorithm for 
guessing the number of clusters as well as cluster center initialization without actually performing K-means, 
under  the  assumption  that  the  clusters  are  well  separated  in  a  certain  way.  The  proposed  algorithm  is 
experimented  on  various  synthetic  data.  The  experimental  results  show  the  effectiveness  of  the  proposed 
approach over the existing. 
},
issn = {1746-7659},
doi = {https://doi.org/2024-JICS-22571},
url = {https://global-sci.com/article/87303/enhanced-k-means-clustering-algorithm-using-a-heuristic-approach}
}