Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data

Article


Ebenuwa, S., Sharif, M., Alazab, Mamoun and Al-Nemrat, A. 2019. Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data. IEEE Access. 7, pp. 24649-24666. https://doi.org/10.1109/ACCESS.2019.2899578
AuthorsEbenuwa, S., Sharif, M., Alazab, Mamoun and Al-Nemrat, A.
Abstract

Data are being generated and used to support all aspects of healthcare provision, from policy formation to the delivery of primary care services. Particularly, with the change of emphasis from curative to preventive medicine, the importance of data-based research such as data mining and machine learning has emphasized the issues of class distributions in datasets. In typical predictive modeling, the inability to effectively address a class imbalance in a real-life dataset is an important shortcoming of the existing machine learning algorithms. Most algorithms assume a balanced class in their design, resulting in poor performance in predicting the minority target class. Ironically, the minority target class is usually the focus in predicting processes. The misclassification of the minority target class has resulted in serious consequences in detecting chronic diseases and detecting fraud and intrusion where positive cases are erroneously predicted as not positive. This paper presents a new attribute selection technique called variance ranking for handling imbalance class problems in a dataset. The results obtained were compared to two well-known attribute selection techniques: the Pearson correlation and information gain technique. This paper uses a novel similarity measurement technique ranked order similarity-ROS to evaluate the variance ranking attribute selection compared to the Pearson correlations and information gain. Further validation was carried out using three binary classifications: logistic regression, support vector machine, and decision tree. The proposed variance ranking and ranked order similarity techniques showed better results than the benchmarks. The ROS technique provided an excellent means of grading and measuring the similarities where other similarity measurement techniques were inadequate or not applicable.

JournalIEEE Access
Journal citation7, pp. 24649-24666
ISSN2169-3536
Year2019
PublisherIEEE
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Anyone
Digital Object Identifier (DOI)https://doi.org/10.1109/ACCESS.2019.2899578
Web address (URL)https://doi.org/10.1109/ACCESS.2019.2899578
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Print25 Feb 2019
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Deposited28 Mar 2019
Accepted21 Jan 2019
Accepted21 Jan 2019
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Islam, S., Naeem, U., Sharif, M. and Dovnarovic, Arnold 2017. CrimeSafe - Helping you stay safe. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers ACM. pp. 642-645
Content Discovery Advertisements: An Explorative Analysis
Jadhav Balaji, R., Baravalle, Andres, Al-Nemrat, A. and Falcarin, P. 2017. Content Discovery Advertisements: An Explorative Analysis. in: Jahankhani, Hamid, Carlile, Alex, Emmett, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World Springer Verlag.
The Future of Enterprise Security with Regards to Mobile Technology and Applications
Tagoe, F. T. and Sharif, M. 2017. The Future of Enterprise Security with Regards to Mobile Technology and Applications. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles
Seuwou, Patrice, Banissi, Ebad, Ubakanma, George, Sharif, M. and Healey, Ann 2017. Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment
Tawil, Abdel-Rahman H., Taweel, Adel, Naeem, U., Montebello, Matthew, Bashroush, R. and Al-Nemrat, A. 2014. Integration operators for generating RDF/OWL-based user defined mediator views in a grid environment. Journal of Intelligent Information Systems. 43 (1), pp. 1-32. https://doi.org/10.1007/s10844-013-0300-5
An efficient system for preprocessing confocal corneal images for subsequent analysis
Sharif, M., Qahwaji, Rami, Hayajneh, Sofyan, Ipson, Stanley, Alzubaidi, Rania and Brahma, Arun 2014. An efficient system for preprocessing confocal corneal images for subsequent analysis. in: 2014 14th UK Workshop on Computational Intelligence (UKCI) IEEE.
Artificial Neural Network-Based System for PET Volume Segmentation
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2010. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging. 2010 (105610). https://doi.org/10.1155/2010/105610
Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2012. Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification. Advances in Fuzzy Systems. 2012 (327861). https://doi.org/10.1155/2012/327861
Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study
Sharif, M., Abbod, Maysam, Sonoda, Luke I. and Sanghera, Bal 2013. Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study. British Journal of Applied Science & Technology. 4 (4), pp. 634-649. https://doi.org/10.9734/bjast/2014/5084
Preparation of 2D sequences of corneal images for 3D model building
Elbita, Abdulhakim, Qahwaji, Rami, Ipson, Stanley, Sharif, M. and Ghanchi, Faruque 2015. Preparation of 2D sequences of corneal images for 3D model building. Computer Methods and Programs in Biomedicine. 114 (2), pp. 194-205. https://doi.org/10.1016/j.cmpb.2014.01.009
Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images
Sharif, M., Qahwaji, R., Ipson, S. and Brahma, A. 2015. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images. Applied Soft Computing. 36 (Nov.), pp. 269-282. https://doi.org/10.1016/j.asoc.2015.07.019
An efficient intelligent analysis system for confocal corneal endothelium images
Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. 2015. An efficient intelligent analysis system for confocal corneal endothelium images. Computer Methods and Programs in Biomedicine. 122 (3), pp. 421-436. https://doi.org/10.1016/j.cmpb.2015.09.003
In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study
Alzubaidi, Rania, Sharif, M., Qahwaji, Rami, Ipson, Stanley and Brahma, Arun 2015. In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study. British Journal of Ophthalmology. 100 (1), pp. 41-55. https://doi.org/10.1136/bjophthalmol-2015-306934
Security countermeasures in the cyber-world
Bendovschi, Andreea and Al-Nemrat, A. 2016. Security countermeasures in the cyber-world. in: 2016 IEEE International Conference on Cybercrime and Computer Forensic (ICCCF) IEEE. pp. 1-7
Measuring sustainability for an effective Information System audit from public organization perspective
Lope Abdul Rahman, Alifah Aida, Islam, S. and Al-Nemrat, A. 2015. Measuring sustainability for an effective Information System audit from public organization perspective. in: Research Challenges in Information Science (RCIS), 2015 IEEE 9th International Conference on IEEE. pp. 42-51
ARP cache poisoning mitigation and forensics investigation
Mangut, Heman Awang, Al-Nemrat, A., Benzaid, Chafika and Tawil, Abdel-Rahman H. 2015. ARP cache poisoning mitigation and forensics investigation. in: 2015 IEEE Trustcom/BigDataSE/ISPA IEEE. pp. 1392-1397
Cybercrime Profiling: Decision-Tree Induction, Examining Perceptions of Internet Risk and Cybercrime Victimisation
Al-Nemrat, A. and Benzaid, Chafika 2015. Cybercrime Profiling: Decision-Tree Induction, Examining Perceptions of Internet Risk and Cybercrime Victimisation. in: 2015 IEEE Trustcom/BigDataSE/ISPA IEEE. pp. 1380-1385
Intelligent Detection of MAC Spoofing Attack in 802.11 Network
Benzaid, Chafika, Boulgheraif, Abderrahman, Dahmane, Fatma Zohra, Al-Nemrat, A. and Zeraoulia, Khaled 2016. Intelligent Detection of MAC Spoofing Attack in 802.11 Network. in: Proceedings of the 17th International Conference on Distributed Computing and Networking ACM.
Forensic Malware Analysis: The Value of Fuzzy Hashing Algorithms in Identifying Similarities
Sarantinos, Nikolaos, Benzaid, Chafika, Arabiat, Omar and Al-Nemrat, A. 2017. Forensic Malware Analysis: The Value of Fuzzy Hashing Algorithms in Identifying Similarities. in: 2016 IEEE Trustcom/BigDataSE/ISPA IEEE. pp. 1782-1787
A Scalable Malware Classification based on Integrated Static and Dynamic Features
Bounouh, Tewfik, Brahimi, Zakaria, Al-Nemrat, A. and Benzaid, Chafika 2017. A Scalable Malware Classification based on Integrated Static and Dynamic Features. 11th International Conference on Global Security, Safety, and Sustainability (ICGS3) 2017. London, UK 18 - 20 Jan 2017 Springer International Publishing. https://doi.org/10.1007/978-3-319-51064-4_10
A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing
Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96. https://doi.org/10.1016/j.procs.2017.08.297
Fast authentication in wireless sensor networks
Benzaid, Chafika, Lounis, Karim, Al-Nemrat, A., Badache, Nadjib and Alazab, Mamoun 2014. Fast authentication in wireless sensor networks. Future Generation Computer Systems. 55, pp. 362-375.
An Analysis of Honeypot Programs and the Attack Data Collected
Moore, C. and Al-Nemrat, A. 2015. An Analysis of Honeypot Programs and the Attack Data Collected. in: Jahankhani, Hamid, Carlile, Alex, Akhgar, Babak, Taal, Amie, Hessami, Ali G. and Hosseinian-Far, Amin (ed.) Global Security, Safety and Sustainability: Tomorrow's Challenges of Cyber Security Springer International Publishing.
Statistical Sampling Approach to Investigate Child Pornography Cases
Sarantinos, N., Al-Nemrat, A. and Naeem, U. 2013. Statistical Sampling Approach to Investigate Child Pornography Cases. 2013 Fourth Cybercrime and Trustworthy Computing Workshop (CTC). Sydney NSW, Australia 21 - 22 Nov 2013 IEEE. https://doi.org/10.1109/CTC.2013.14