Name
Title | ||
|---|---|---|
Simultaneous Feature Selection and Heterogeneity Control for SVM Classification: An Application to Mental Workload Assessment |
Abstract | ||
|---|---|---|
•Novel SVM-based approach for binary classification.•Procedure pools information across users in a single optimization problem.•Sources of information are penalized using a group penalty function.•The proposal is successfully applied in a mental-workload assessment task. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2019.112988 | Expert Systems with Applications |
Keywords | DocType | Volume |
Support vector machines,Feature selection,Heterogeneity control,Mental workload,Group penalty functions | Journal | 143 |
ISSN | Citations | PageRank |
0957-4174 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sebastián Maldonado | 1 | 508 | 32.45 |
| Julio López | 2 | 124 | 13.49 |
| Angel Jimenez-Molina | 3 | 46 | 4.75 |
| Hernán Lira | 4 | 0 | 0.34 |