A New Clustering Algorithm Partition K-Means
K-means is a classic algorithm of partition clustering, its speed is very fast, well, the clustering result is very sensitive to the initial cores. As a result, algorithm K-means does not always get the Global Optimization. To solve this problem, this paper proposes a new algorithm partition K-means, which selects the initial cores with a partition method and then cluster the data set with K-means. The experiment shows that the new algorithm gets better effect and better efficiency than the original algorithm K-means.
M. Chen et al., "A New Clustering Algorithm Partition K-Means", Key Engineering Materials, Vols. 474-476, pp. 577-580, 2011