Citation

Chang, Timothy Zhi Wei and Sim, Kok Swee and Tan, Shing Chiang (2022) Adversarial Networks in Data Classification. In: 2nd FET PG Engineering Colloquium Proceedings 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

Text 30_Timothy Chang_PPM Extended Abstract_Second Half 2022.pdf Restricted to Registered users only Download (66kB)

Abstract

Real datasets which were obtained from public and commercial portals were compiled and studied. A generative adversarial network variant, WGAN-GP is adopted for generating additional minority samples with the use of Fuzzy ARTMAP was designed and the performance was rigorously evaluated through a performance comparison with other state-of-the-art machine learning models with their respective datasets. Another experiment was conducted using SMOTE and Gaussian SMOTE are used to generate minority class samples to balance the data set. Fuzzy ARTMAP was used as the classifier with its ability to overcome the stability-plasticity dilemma.

Item Type:	Conference or Workshop Item (Other)
Uncontrolled Keywords:	Imbalanced data classification, power systems, condition monitoring, SMOTE, Fuzzy ARTMAP
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	20 Feb 2023 09:29
Last Modified:	20 Feb 2023 09:29
URII:	http://shdl.mmu.edu.my/id/eprint/11139

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