Name
Abstract | ||
|---|---|---|
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Bayesian approach to a segmentation model based on the switching linear Gaussian ... |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICMLA.2008.40 | ICMLA |
Keywords | Field | DocType |
clustering approach,time-series segmentation,bayesian approach,cancer patients,prognostic systems,unsupervised scenario,linear gaussian,fundamental problem,segmentation model,statistical analysis,clustering algorithms,cancer,hierarchical clustering,clustering,survival function | Metastasis,Lung cancer,Hierarchical clustering,Data mining,Survival function,Computer science,Artificial intelligence,Cluster analysis,Machine learning,Lymph node,Cancer,Statistical analysis | Conference |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dechang Chen | 1 | 402 | 33.51 |
| Xing Kai | 2 | 442 | 28.13 |
| Donald Henson | 3 | 12 | 1.87 |
| Li Sheng | 4 | 70 | 8.34 |
| Arnold M. Schwartz | 5 | 14 | 2.43 |
| Xiuzhen Cheng | 6 | 3238 | 210.23 |