Name
Abstract | ||
|---|---|---|
Data clustering is a common unsupervised learning method frequently used in exploratory data analysis. However, identifying relevant structures in unlabeled, high-dimensional data is nontrivial, requiring iterative experimentation with clustering parameters as well as data features and instances. The number of possible clusterings for a typical dataset is vast, and navigating in this vast space is... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TVCG.2018.2864477 | IEEE Transactions on Visualization and Computer Graphics |
Keywords | DocType | Volume |
Tools,Data visualization,Visualization,Clustering algorithms,Data analysis,Space exploration,Dimensionality reduction | Journal | 25 |
Issue | ISSN | Citations |
1 | 1077-2626 | 14 |
PageRank | References | Authors |
0.48 | 29 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Cavallo | 1 | 39 | 5.57 |
| Çagatay Demiralp | 2 | 235 | 29.10 |