Introduction - If you have any usage issues, please Google them yourself
Algorithm k-means is a simple iterative clustering algorithm, which divides the set of data to a user-specified number of clusters, k. The algorithm is simple to implement and run relatively fast, easily adaptable and common in practice. It is historically one of the most important data mining algorithms.
Historically, that the K-means was discovered by several researchers various disciplines, especially Lloyd (1957, 1982), Forge (1965), Friedman and Rubin (1967), and McQueen (1967). Detailed history of K-means together with a description of various changes and given Jane Dubs.