K-Harmonic Means Clustering with Simulated Annealing
基于模拟退火的K调和均值聚类算法

K-means algorithm is a frequently-used methods of partition clustering.However,it greatly depends on the initial values and converges to local minimum.In K-harmonic means clustering,harmonic means fuction which apply distance from the data point to all clustering centers is used to solves the problem that clustering result is sensitive to the initial valve instead of the minimum distance.Although the problem above is solved,the problem converged to local minimum is still existed.In order to obtain a glonal ...