Name
Abstract | ||
|---|---|---|
DenStream is a data stream clustering algorithm which has been widely studied due to its ability to find clusters with arbitrary shapes and dealing with noisy objects. In this paper, we propose a different approach for pruning micro-clusters in DenStream. Our proposal unlike other previously reported pruning, introduces a different way for computing the micro-cluster radii and provides new options for the pruning stage of DenStream. From our experiments over public standard datasets we conclude that our approach improves the results obtained by DenStream. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19264-2_4 | MCPR |
Keywords | Field | DocType |
Clustering, Data streams, Data mining | Cluster (physics),Data mining,Data stream mining,Data stream clustering,Pattern recognition,Correlation clustering,Computer science,Artificial intelligence,Pruning (decision trees),Cluster analysis,Machine learning,Pruning | Conference |
Volume | ISSN | Citations |
9116 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Argenis A. Aroche-Villarruel | 1 | 1 | 0.70 |
| José Francisco Martínez Trinidad | 2 | 446 | 44.72 |
| Jesús Ariel Carrasco-Ochoa | 3 | 493 | 59.65 |
| Airel Pérez Suárez | 4 | 32 | 3.07 |