Name
Abstract | ||
|---|---|---|
•Four hybrid feature selection methods for classification task are proposed.•Our hybrid method combines Whale Optimization Algorithm with simulated annealing.•Eighteen UCI datasets were used in the experiments.•Our approaches result a higher accuracy by using less number of features. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.neucom.2017.04.053 | Neurocomputing |
Keywords | Field | DocType |
Feature selection,Hybrid optimization,Whale Optimization Algorithm,Simulated annealing,Classification,WOA,Optimization | Memetic algorithm,Simulated annealing,Data mining,Feature vector,Pattern recognition,Feature selection,Artificial intelligence,Optimization algorithm,Mathematics,Machine learning,Metaheuristic | Journal |
Volume | ISSN | Citations |
260 | 0925-2312 | 67 |
PageRank | References | Authors |
1.36 | 31 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Majdi Mafarja | 1 | 574 | 20.00 |
| Seyedali Mirjalili | 2 | 3949 | 140.80 |