Name
Title | ||
|---|---|---|
A partitional clustering algorithm validated by a clustering tendency index based on graph theory |
Abstract | ||
|---|---|---|
Applying graph theory to clustering, we propose a partitional clustering method and a clustering tendency index. No initial assumptions about the data set are requested by the method. The number of clusters and the partition that best fits the data set, are selected according to the optimal clustering tendency index value. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1016/j.patcog.2005.10.027 | Pattern Recognition |
Keywords | Field | DocType |
partitional clustering method,initial assumption,clustering tendency index,graph theory,partitional clustering algorithm,optimal clustering tendency index,indexation,clustering algorithms,unsupervised learning | Fuzzy clustering,Data mining,CURE data clustering algorithm,Artificial intelligence,Cluster analysis,Single-linkage clustering,k-medians clustering,Data stream clustering,Pattern recognition,Correlation clustering,Determining the number of clusters in a data set,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 5 | Pattern Recognition |
Citations | PageRank | References |
8 | 0.72 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Helena Brás Silva | 1 | 8 | 0.72 |
| Paula Brito | 2 | 144 | 11.29 |
| Joaquim Pinto Da Costa | 3 | 262 | 14.82 |