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Dr. Sajid Anwar
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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
3462016
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
3072017
Customer churn prediction in telecommunication industry using data certainty
A Amin, F Al-Obeidat, B Shah, A Adnan, J Loo, S Anwar
Journal of Business Research 94, 290-301, 2019
2962019
Static malware detection and attribution in android byte-code through an end-to-end deep system
M Amin, TA Tanveer, M Tehseen, M Khan, FA Khan, S Anwar
Future generation computer systems 102, 112-126, 2020
1182020
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
1172019
Automated GUI test coverage analysis using GA
A Rauf, S Anwar, MA Jaffer, AA Shahid
2010 Seventh International Conference on Information Technology: New …, 2010
822010
Android malware detection through generative adversarial networks
M Amin, B Shah, A Sharif, T Ali, KI Kim, S Anwar
Transactions on Emerging Telecommunications Technologies 33 (2), e3675, 2022
682022
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
602015
The effective use of information technology and interactive activities to improve learner engagement
A Ullah, S Anwar
Education Sciences 10 (12), 349, 2020
592020
Software component selection based on quality criteria using the analytic network process
S Nazir, S Anwar, SA Khan, S Shahzad, M Ali, R Amin, M Nawaz, ...
Abstract and Applied Analysis 2014, 2014
492014
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
482023
A novel learning method to classify data streams in the internet of things
MA Khan, A Khan, MN Khan, S Anwar
2014 national software engineering conference, 61-66, 2014
482014
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 (6), 3924-3948, 2020
472020
COVID-19 patient count prediction using LSTM
M Iqbal, F Al-Obeidat, F Maqbool, S Razzaq, S Anwar, A Tubaishat, ...
IEEE Transactions on Computational Social Systems 8 (4), 974-981, 2021
462021
Conceptualization of smartphone usage and feature preferences among various demographics
ZH Ahmar Rashid, Muhammad Amir Zeb,Amad Rashid, Sajid Anwar, Fernando Joaquim
Cluster Computing, 2020
452020
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
Intrusion detection in networks using cuckoo search optimization
M Imran, S Khan, H Hlavacs, FA Khan, S Anwar
Soft Computing 26 (20), 10651-10663, 2022
422022
A deep learning system for health care IoT and smartphone malware detection
M Amin, D Shehwar, A Ullah, T Guarda, TA Tanveer, S Anwar
Neural Computing and Applications, 1-12, 2022
412022
Effects of Banadiq-al Buzoor in some renal disorders
S Anwar, NA Khan, KMY Amin, G Ahmad
Hamdard Medicus 42 (4), 31-36, 1999
391999
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
372018
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Articles 1–20