Name
Abstract | ||
|---|---|---|
This paper proposes a novel undersampling method, for dealing with imbalanced datasets. The proposal is based on a novel instance importance measure (also introduced in this paper), and is able to balance hybrid and incomplete data. The numerical experiments carried out show the proposed undersampling algorithm outperforms others algorithms of the state of art, in well-known imbalanced datasets. |
Year | Venue | Keywords |
|---|---|---|
2020 | JOURNAL OF UNIVERSAL COMPUTER SCIENCE | undersampling,imbalanced data,hybrid and incomplete data |
DocType | Volume | Issue |
Journal | 26 | 6 |
ISSN | Citations | PageRank |
0948-695X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oscar Camacho Nieto | 1 | 65 | 14.93 |
| Cornelio Yáñez-Márquez | 2 | 0 | 0.34 |
| Yenny Villuendas-rey | 3 | 46 | 14.38 |