| 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 | 14 | 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 | 12 | 2022 |
| Improving random forest algorithm by selecting appropriate penalized method Z Farhadi, H Bevrani, MR Feizi-Derakhshi Communications in Statistics-Simulation and Computation 53 (9), 4380-4395, 2024 | 11 | 2024 |
| 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 | 6 | 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 | 5 | 2024 |
| An ensemble-based model for sentiment analysis of persian comments on instagram using deep learning algorithms S Eyvazi-Abdoljabbar, SK Kim, MR Feizi-Derakhshi, Z Farhadi, ... IEEE Access, 2024 | 3 | 2024 |
| ADeFS: A Deep Forest Regression-Based Model to Enhance the Performance Based on LASSO and Elastic Net Z Farhadi, MR Feizi-Derakhshi, I Khalaf Salman Al-Tameemi, W Kim Mathematics 13 (1), 118, 2024 | | 2024 |
Mohammad-Reza Feizi-DerakhshiFull Professor of Artificial Intelligence, Department of Computer Engineering, University of Tabrizایمیل تأیید شده در tabrizu.ac.ir