Ikuti
Adnan Amin , Ph.D.
Adnan Amin , Ph.D.
School of Computer Science and I.T., Institute of Management Sciences Peshawar, PK
Email yang diverifikasi di imsciences.edu.pk - Beranda
Judul
Dikutip oleh
Dikutip oleh
Tahun
Comparing oversampling techniques to handle the class imbalance problem: A customer churn prediction case study
A Amin, S Anwar, A Adnan, M Nawaz, N Howard, J Qadir, A Hawalah, ...
Ieee Access 4, 7940-7957, 2016
3442016
Customer churn prediction in the telecommunication sector using a rough set approach
A Amin, S Anwar, A Adnan, M Nawaz, K Alawfi, A Hussain, K Huang
Neurocomputing 237, 242-254, 2017
3012017
Customer churn prediction in telecommunication industry using data certainty
A Adnan, AO Feras, S Babar, A Awais, L Jonathan, A Sajid
Journal of Business Research, 2018
2972018
Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods
A Amin, B Shah, AM Khattak, FJL Moreira, G Ali, A Rocha, S Anwar
International Journal of Information Management 46, 304-319, 2019
1192019
Churn prediction in telecommunication industry using rough set approach
A Amin, S Shehzad, C Khan, I Ali, S Anwar
New trends in computational collective intelligence, 83-95, 2015
622015
An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes
A Amin, A Adnan, S Anwar
Applied Soft Computing 137, 110103, 2023
502023
Just-in-time customer churn prediction in the telecommunication sector
A Amin, F Al-Obeidat, B Shah, MA Tae, C Khan, HUR Durrani, S Anwar
The Journal of Supercomputing 76, 3924-3948, 2020
472020
Customer churn prediction in telecommunication industry: With and without counter-example
A Amin, C Khan, I Ali, S Anwar
Nature-Inspired Computation and Machine Learning: 13th Mexican International …, 2014
452014
Just-in-time customer churn prediction: With and without data transformation
A Amin, B Shah, AM Khattak, T Baker, S Anwar
2018 IEEE congress on evolutionary computation (CEC), 1-6, 2018
362018
A comparison of two oversampling techniques (smote vs mtdf) for handling class imbalance problem: A case study of customer churn prediction
A Amin, F Rahim, I Ali, C Khan, S Anwar
New Contributions in Information Systems and Technologies: Volume 1, 215-225, 2015
312015
Compromised user credentials detection in a digital enterprise using behavioral analytics
S Shah, B Shah, A Amin, F Al-Obeidat, F Chow, FJL Moreira, S Anwar
Future Generation Computer Systems 93, 407-417, 2019
302019
A multilayer prediction approach for the student cognitive skills measurement
S Ahmad, K Li, A Amin, MS Anwar, W Khan
IEEE Access 6, 57470-57484, 2018
252018
A systematic analysis of link prediction in complex network
H Gul, A Amin, A Adnan, K Huang
IEEE Access 9, 20531-20541, 2021
222021
Site selection for food distribution using rough set approach and TOPSIS method
C Khan, S Anwar, S Bashir, A Rauf, A Amin
Journal of Intelligent & Fuzzy Systems, 1-7, 2015
212015
A prudent based approach for customer churn prediction
A Amin, F Rahim, M Ramzan, S Anwar
International conference: Beyond databases, architectures and structures …, 2015
212015
Features weight estimation using a genetic algorithm for customer churn prediction in the telecom sector
A Amin, B Shah, A Abbas, S Anwar, O Alfandi, F Moreira
New Knowledge in Information Systems and Technologies: Volume 2, 483-491, 2019
202019
Classification of cyber attacks based on rough set theory
A Amin, S Anwar, A Adnan, MA Khan, Z Iqbal
2015 First International Conference on Anti-Cybercrime (ICACC), 1-6, 2015
172015
A prudet based approach for compromised user credentials detection
A Amin, B Shah, S Anwar, F Al-Obeidat, AM Khattak, A Adnan
Cluster Computing, 1-19, 2017
132017
Deep network for the iterative estimations of students’ cognitive skills
S Ahmad, MS Anwar, M Ebrahim, W Khan, K Raza, SH Adil, A Amin
IEEE Access 8, 103100-103113, 2020
122020
A systematic analysis of community detection in complex networks
H Gul, F Al-Obeidat, A Amin, M Tahir, F Moreira
Procedia Computer Science 201, 343-350, 2022
92022
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