K-means algorithm----读书笔记

    The K-means algorithm is based on the use of squared Euclidean distance as the measure of 

dissimilarity between a data point and a prototype vector. We can then define an objective function,

sometimes called a distortion measure, given by 

    J=Σ_n=1Σ_k=1r_nk||x_n-μ_k||²,where n=1,...N, k=1,...,K, N is observations of a random D-dimensional

Euclidean variable x, K is number of clusters. J represents the sum of the squares of the distances of

each data point to its assigned vector μ_k.