Name
Abstract | ||
|---|---|---|
In this study, we address the problem of finding the optimal number of clusters on incomplete data using cluster validity functions. Experiments were performed on different data sets in order to analyze to what extent cluster validity indices adapted to incomplete data can be used for validation of clustering results. Moreover we analyze which fuzzy clustering algorithm for incomplete data produces better partitioning results for cluster validity. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33362-0_50 | SUM |
Keywords | Field | DocType |
partitioning result,different data set,extent cluster validity,cluster validity,incomplete data,optimal number,fuzzy clustering algorithm,clustering result,cluster validity function | k-medians clustering,Cluster (physics),Data mining,Fuzzy clustering,Data set,Pattern recognition,Computer science,Artificial intelligence,Cluster analysis | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ludmila Himmelspach | 1 | 24 | 4.62 |
| João Paulo Carvalho | 2 | 110 | 17.52 |
| Stefan Conrad | 3 | 0 | 0.34 |