K-means clustering is a partitioning method and as anticipated, this method decomposes a dataset into a set of disjoint clusters. Given a dataset, a partitioning method constructs several partitions of this data, with each partition representing a cluster. These methods relocate instances by moving them from one cluster to another, starting from an initial partitioning.
Partitioning-based clustering methods - K-means algorithm
The K-means algorithm
The K-means algorithm is a clustering algorithm designed in 1967 by MacQueen which allows the dividing of groups of objects into K partitions based on their attributes. It is a variation of the expectation-maximization (EM) algorithm, whose goal is to determine the K data groups...
