Importance of Initialization in K-Means Clustering
Author:
Affiliation:
1. Delhi Technological University,Dept. of Software Engineering,Delhi,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9807685/9807649/09807996.pdf?arnumber=9807996
Reference20 articles.
1. Least squares quantization in PCM
2. Clustering to minimize the maximum intercluster distance
3. New Fast K-Means Clustering Algorithm Using Modified Centroid Selection Method;sujatha;International Journal of Engineering Research & Technology (IJERT),2013
4. Survey on Exiting Method for Selecting Initial Centroids in K-means Clustering;kodinariya;International Journal of Engineering Development and Research,2014
5. New Method for Finding Initial Cluster Centroids in K-means Algorithm
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