According to the formal definition of K-means clustering – K-means clustering is an iterative algorithm that partitions a group of data containing n values into k subgroups. Each of the n value belongs to the k cluster with the nearest mean.
K-means clustering is the most popular form of an unsupervised learning algorithm. It is easy to understand and implement.
