K means method 逐步聚类法 ; 慢慢聚类法
k-means method k均值法
K-means clustering method 均值聚类
K-means Cluster method k均值聚类法则
Experiments using artificial data and actual business data testify the validity of this method. It can improve the traditional K-means effect well.
采用人工数据和实际商业数据的实验证明该方法能有效地改善传统的聚类效果。
The clustering method based on partitioning is mainly included K-Means and K-Medoids; the other methods are the mutation of these two methods.
基于划分的聚类算法主要有K均值和K中心点算法，其他的方法都是这两种算法的变种。
The function model of the multiquadric's central node to choose to do an in-depth discussion, put forward the "Adaptive location" to match the characteristics of the K-means clustering method.
对函数模型法中的多面函数中心节点的选择做了深入讨论，提出了具有“位置自适应”匹配特点的K均值聚类法。
应用推荐