一种改进的K-means算法

K-means算法以其简单性和快速性在文本聚类中得到广泛应用,但是传统的K-means算法对初值的依赖性很强,需要事先给出要生成的簇的数目k,而这个参数k的确定一般是根据用户的经验知识给出的;另外,其初始聚类中心是随机选取的,这种随机性往往导致聚类结果的不德定.可以说,不同的k值和不同的初始聚类中心对聚类质量和时间效率...

An Improved K-means Algorithm

K-means algorithm with its simplicity and rapidity is widely used in the text clustering.However,the traditional K-means algorithm was highly dependent on the initial value,and itneeds to give the parameter k in advance,which is always determined by knowledge andexperience of users.In addition,the initial cluster centers of it are randomly selected,thisrandomness offen led to instability of clustering results.So to speak,the different k values anddifferent initial cluster centers had a great impact on clust...