希望alink 加入 层次聚类(hierarchical cluster)的功能实现

[zsz00]

希望alink 加入 层次聚类的功能实现 . 主要是 凝聚的层次聚类算法: 最小距离,平均距离,最大距离的层次聚类.

层次聚类方法在某些数据挖掘场景中可能是比 k-means更通用和有效的聚类方法, 希望社区有人可以加入此方法的实现, 或者提出相关计划..

[lqb11]

二分kmeans也是一种由顶向下的层次聚类，可以试用下这个算法

[Pratham31]

But When you compare K means and Hierarchical Clustering You will find that K-means Computationally Fast than Hierarchical. As K-means takes O(n) complexity while Hierarchical takes O(n x n) complexity. And yes Plus point of Hierarchical clustering is that it is good for presentation purpose when the dataset is too small with the help of Dendrograms. I will try to implement it soon :)