Name
Abstract | ||
|---|---|---|
Rare classes are usually hidden in an imbalanced dataset with the majority of the data examples from major classes. Rare-class mining (RCM) aims at extracting all the data examples belonging to rare classes. Most of the existing approaches for RCM require a certain amount of labeled data examples as input. However, they are ineffective in practice since requesting label information from domain exp... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCYB.2019.2924804 | IEEE Transactions on Cybernetics |
Keywords | DocType | Volume |
Anomaly detection,Diseases,Vegetation,Approximation algorithms,Time complexity,Computer science | Journal | 51 |
Issue | ISSN | Citations |
10 | 2168-2267 | 0 |
PageRank | References | Authors |
0.34 | 12 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haiqin Weng | 1 | 5 | 3.72 |
| Shouling Ji | 2 | 83 | 20.52 |
| Changchang Liu | 3 | 42 | 6.34 |
| Ting Wang | 4 | 664 | 65.43 |
| Qinming He | 5 | 371 | 41.53 |
| Jianhai Chen | 6 | 140 | 16.34 |