International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 29 - Number 7 |
Year of Publication: 2011 |
Authors: Mohammad F. Eltibi, Wesam M. Ashour |
10.5120/3573-4930 |
Mohammad F. Eltibi, Wesam M. Ashour . Initializing K-Means Clustering Algorithm using Statistical Information. International Journal of Computer Applications. 29, 7 ( September 2011), 51-55. DOI=10.5120/3573-4930
K-means clustering algorithm is one of the best known algorithms used in clustering; nevertheless it has many disadvantages as it may converge to a local optimum, depending on its random initialization of prototypes. We will propose an enhancement to the initialization process of k-means, which depends on using statistical information from the data set to initialize the prototypes. We show that our algorithm gives valid clusters, and that it decreases error and time.