# Hierarchical Clustering

Posted by GwanSiu on December 7, 2018

## 1. Introducation to Hierarchical Clustering

Clustering algorithm is a process to group similar object together. From the view of ininput type, clustering algorithm can be divied into two categories: similarity-based clustering and feature-based clustering. In similarity-based clustering, the input is $N\times N$ dissimilarity matrix or distance matrix $D$. In feature-based clustering, the input is $N\times D$ feature matrix. From the view of output, partitional clustering and hierarchical clustering are two kinds of clustering algorithm. In this article, I will talk about hierarchical clustering, figure 1 is shown the structure of hierarchical clustering. Hierarchies are commonly used to organize information. There are two kinds structures of hierarchical clustering: bottom-up agglomerative clustering, top-bottom divise.

## Reference

[1] Robert C. Machine learning, a probabilistic perspective[J]. 2014. [2] Lecture:Clustering and Distance Metrics, 10701-Introduction to machine learning, Eric Xing