Mastering Machine Learning with scikit-learn - Second Edition

K-means

The K-means algorithm is a clustering method that is popular because of its speed and scalability. K-means is an iterative process of moving the centers of the clusters, called the centroids, to the mean position of their constituent instances and re-assigning instances to the clusters with the closest centroids. The titular k is a hyperparameter that specifies the number of clusters that should be created; K-means automatically assigns observations to clusters but cannot determine the appropriate number of clusters. k must be a positive integer that is less than the number of instances in the training set. Sometimes the number of clusters is specified by the clustering problem's context. For example, a company that manufactures shoes ...