Name
Title | ||
|---|---|---|
Interpreting and Extending Classical Agglomerative Clustering Algorithms using a Model-Based approach |
Abstract | ||
|---|---|---|
We present two results which arise from a model-based approach to hierarchical agglom- erative clustering. First, we show formally that the common heuristic agglomerative clustering algorithms - single-link, complete-link, group- average, and Ward's method - are each equiva- lent to a hierarchical model-based method. This interpretation gives a theoretical explanation of the empirical behavior of these algorithms, as well as a principled approach to resolving practical issues, such as number of clusters or the choice of method. Second, we show how a model-based approach can be used to extend these basic agglomerative algorithms. We intro- duce adjusted complete-link, Mahalanobis-link, and line-link as variants of the classical agglom- erative methods, and demonstrate their utility. |
Year | Venue | Keywords |
|---|---|---|
2002 | ICML | extending classical agglomerative clustering,model-based approach,data mining,hierarchical model,computer science |
Field | DocType | ISBN |
Data mining,Computer science,Autonomous system (Internet),Artificial intelligence,Hierarchical database model,Single-linkage clustering,Hierarchical clustering,Heuristic,Hierarchical clustering of networks,Algorithm,Ward's method,Brown clustering,Machine learning | Conference | 1-55860-873-7 |
Citations | PageRank | References |
35 | 2.45 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sepandar D. Kamvar | 1 | 2710 | 197.74 |
| Dan Klein | 2 | 8083 | 495.21 |
| Christopher D. Manning | 3 | 22579 | 1126.22 |