| Improving random forest algorithm by selecting appropriate penalized method Z Farhadi, H Bevrani, MR Feizi-Derakhshi Communications in Statistics-Simulation and Computation, 1-16, 2022 | 6 | 2022 |
| Combining regularization and dropout techniques for deep convolutional neural network Z Farhadi, H Bevrani, MR Feizi-Derakhshi 2022 global energy conference (GEC), 335-339, 2022 | 6 | 2022 |
| An ensemble framework to improve the accuracy of prediction using clustered random-forest and shrinkage methods Z Farhadi, H Bevrani, MR Feizi-Derakhshi, W Kim, MF Ijaz Applied Sciences 12 (20), 10608, 2022 | 6 | 2022 |
| Analysis of penalized regression methods in a simple linear model on the high-dimensional data Z Farhadi, RA Belaghi, OG Alma American Journal of Theoretical and Applied Statistics 8 (5), 185-192, 2019 | 4 | 2019 |
| ERDeR: The combination of statistical shrinkage methods and ensemble approaches to improve the performance of deep regression Z Farhadi, MR Feizi-Derakhshi, H Bevrani, W Kim, MF Ijaz IEEE Access, 2024 | | 2024 |
Mohammad-Reza Feizi-DerakhshiFull Professor of Computer Engineering, University of TabrizVerified email at tabrizu.ac.ir
