Research of clustering algorithm based on K-means

Original k-means clustering algorithm is the means that selects K centers randomly from the data sample cluster.This selection is blind and random,and to a certain extent the validity of algorithm lies on the selection.In order to avoid the blindness of selection,we should make full use of the information of existing data sample dot.We make pre-treatment of the data to choose the initial center.The experiment improves not only the calculation efficiency of algorithm,but also the precision of ultimate clustering.