Introduction to K-means cluster algorithm

What is k-means?

K-meansAlgorithmThe process is as follows. First, K objects are randomly selected from n data objects as the initial cluster center. For all other objects, the similarity (distance) between these objects and the cluster center is determined ), they are assigned to the most similar (represented by the cluster center) clusters. Then calculate the clustering center of each new cluster (the mean of all objects in the cluster), and repeat the process until the standard measure function starts to converge. Generally, the mean variance is used as the standard measure function. K-means is sensitive to input data, especially the selection of the initial cluster center.