An Improved Algorithm of k-means
Yeli Li · Journal of Beijing Institute of Graphic Communication · 2007
K-means algorithm is a widely used partition method in clustering.The algorithm is suitable for the spherical wave data.The algorithm has a good result for spherical,protruding data.However,the algorithm has its prominent limitations.A small number of isolated points would have a considerable impact on the clustering results.This paper study presents an idea to separate the clustering centroid from the clustering seed and completes an algorithm based on this idea,improving the k-means algorithm.It also provides a specific ideology based on the k-means algorithm to improve the algorithm.The paper presents the results of the experiments to prove that this algorithm is more veracious than the k-means algorithm.