| Penalized logistic regression with the adaptive LASSO for gene selection in high-dimensional cancer classification ZY Algamal, MH Lee Expert Systems with Applications 42 (23), 9326-9332, 2015 | 194 | 2015 |
| Regularized logistic regression with adjusted adaptive elastic net for gene selection in high dimensional cancer classification ZY Algamal, MH Lee Computers in biology and medicine 67, 136-145, 2015 | 139 | 2015 |
| Feature selection using particle swarm optimization-based logistic regression model OS Qasim, ZY Algamal Chemometrics and Intelligent Laboratory Systems 182, 41-46, 2018 | 96 | 2018 |
| Improved Slime Mould Algorithm based on Firefly Algorithm for feature selection: A case study on QSAR model AA Ewees, L Abualigah, D Yousri, ZY Algamal, MAA Al-Qaness, ... Engineering with Computers, 1-15, 2021 | 92 | 2021 |
| A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification ZY Algamal, MH Lee Advances in data analysis and classification 13 (3), 753-771, 2019 | 92 | 2019 |
| High‐dimensional QSAR prediction of anticancer potency of imidazo [4, 5‐b] pyridine derivatives using adjusted adaptive LASSO ZY Algamal, MH Lee, AM Al‐Fakih, M Aziz Journal of Chemometrics 29 (10), 547-556, 2015 | 85 | 2015 |
| Boosting arithmetic optimization algorithm with genetic algorithm operators for feature selection: case study on cox proportional hazards model AA Ewees, MAA Al-Qaness, L Abualigah, D Oliva, ZY Algamal, AM Anter, ... Mathematics 9 (18), 2321, 2021 | 80 | 2021 |
| Classification of Breast Cancer Histopathology Images based on Adaptive Sparse Support Vector Machine MA Kahya, W Al-Hayani, ZY Algamal Journal of Applied Mathematics & Bioinformatics 7 (1), 49-69, 2017 | 80 | 2017 |
| A new hybrid firefly algorithm and particle swarm optimization for tuning parameter estimation in penalized support vector machine with application in chemometrics NA Al-Thanoon, OS Qasim, ZY Algamal Chemometrics and Intelligent Laboratory Systems 184, 142-152, 2019 | 79 | 2019 |
| Developing a ridge estimator for the gamma regression model ZY Algamal Journal of Chemometrics 32 (10), e3054, 2018 | 70 | 2018 |
| Tuning parameter estimation in SCAD-support vector machine using firefly algorithm with application in gene selection and cancer classification NA Al-Thanoon, OS Qasim, ZY Algamal Computers in biology and medicine 103, 262-268, 2018 | 61 | 2018 |
| Feature selection based on chaotic binary black hole algorithm for data classification OS Qasim, NA Al-Thanoon, ZY Algamal Chemometrics and Intelligent Laboratory Systems 204, 104104, 2020 | 60 | 2020 |
| Quantitative structure–activity relationship model for prediction study of corrosion inhibition efficiency using two‐stage sparse multiple linear regression AM Al‐Fakih, ZY Algamal, MH Lee, HH Abdallah, H Maarof, M Aziz Journal of Chemometrics 30 (7), 361–368, 2016 | 58 | 2016 |
| A new ridge estimator for the Poisson regression model NK Rashad, ZY Algamal Iranian Journal of Science and Technology, Transactions A: Science 43, 2921-2928, 2019 | 57 | 2019 |
| Diagnostic in poisson regression models ZY Algamal Electronic Journal of Applied Statistical Analysis 5 (2), 178-186, 2012 | 54 | 2012 |
| Proposed methods in estimating the ridge regression parameter in Poisson regression model MM Alanaz, ZY Algamal Electronic Journal of Applied Statistical Analysis 11 (2), 505-515, 2018 | 53 | 2018 |
| Shrinkage estimators for gamma regression model ZY Algamal Electronic Journal of Applied Statistical Analysis 11 (1), 253-268, 2018 | 52 | 2018 |
| Liu-type estimator for the gamma regression model ZY Algamal, Y Asar Communications in Statistics-Simulation and Computation 49 (8), 2035-2048, 2020 | 50 | 2020 |
| High dimensional QSAR study of mild steel corrosion inhibition in acidic medium by furan derivatives AM Al-Fakih, M Aziz, HH Abdallah, ZY Algamal, MH Lee, H Maarof International Journal of Electrochemical Science 10 (4), 3568-3583, 2015 | 49 | 2015 |
| Improving grasshopper optimization algorithm for hyperparameters estimation and feature selection in support vector regression ZY Algamal, MK Qasim, MH Lee, HTM Ali Chemometrics and Intelligent Laboratory Systems 208, 104196, 2021 | 48 | 2021 |
