Name
Abstract | ||
|---|---|---|
This paper studies the estimation of the number of clusters using the so-called stability-based approach, where clusters obtained for two subsets of the dataset are compared via a similarity index and the decision regarding the number of clusters is taken based on the statistics of the index over randomly selected subsets. We introduce a new similarity index s(., .), and analyze the consistency of the estimator of the number of classes when k-means algorithm is used in conjunction with s(., .). Various similarity indices are experimentally evaluated when comparing the "true" data partition with the partition obtained at each level of a hierarchical clustering tree. Finally, experimental results with real data are reported for a glioma microarray dataset. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ISSPA.2003.1224814 | SEVENTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOL 2, PROCEEDINGS |
Keywords | Field | DocType |
cancer,signal processing,stability analysis,clustering algorithms,algorithm design and analysis,statistics,hierarchical clustering,cluster analysis,shape,microarray data,indexation,testing,k means algorithm,stability,statistical analysis | Hierarchical clustering,k-means clustering,Cluster (physics),Algorithm design,Pattern recognition,Computer science,Microarray analysis techniques,Artificial intelligence,Cluster analysis,Partition (number theory),Estimator | Conference |
Citations | PageRank | References |
7 | 1.06 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ciprian Doru Giurcaneanu | 1 | 43 | 12.44 |
| Ioan Tabus | 2 | 276 | 38.23 |
| Ilya Shmulevich | 3 | 1166 | 100.48 |
| Wei Zhang | 4 | 1221 | 180.16 |