Name
Abstract | ||
|---|---|---|
This paper proposes a fuzzy partitioning subspace clustering algorithm that minimizes a variant of the FCM cost function with a weighted Euclidean distance and a penalty term. To this aim it considers the framework of proximal optimization. It establishes the expression of the proximal operator for the considered cost function and derives PFSCM, an algorithm combining proximal descent and alternate optimization. Experiments show the relevance of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-40596-4_56 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Fuzzy partitioning clustering,Subspace clustering,Proximal descent | Subspace clustering,Pattern recognition,Correlation clustering,Euclidean distance,Proximal Gradient Methods,Fuzzy subspace,Artificial intelligence,Operator (computer programming),Cluster analysis,Mathematics,Fuzzy partitioning | Conference |
Volume | ISSN | Citations |
610 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arthur Guillon | 1 | 0 | 0.34 |
| Marie-Jeanne Lesot | 2 | 220 | 32.41 |
| Christophe Marsala | 3 | 237 | 34.77 |
| Nikhil R. Pal | 4 | 4464 | 417.55 |