Arkok, Bassam and Zeki, Akram M. (2022) GOS: a Genetic OverSampling Algorithm for classification of Quranic verses. In: The 13th International Conference on Information & Communication Systems, 21-23 June 2022, Jordan.
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Abstract
Imbalanced classes problem is a problem in many datasets in real applications, where one class “minority class" contains few numbers of samples and the other "majority class" contains many numbers of samples. It is difficult to build a training model to classify the imbalanced classes correctly due to tending the accuracy of the classification of the majority class. In this paper, a new technique called "GOS: a Genetic OverSampling algorithm”, is proposed using a genetic algorithm. A genetic algorithm is applied to oversample the imbalanced datasets and to improve the performance of imbalanced classification. This improvement is achieved due to adjusting the locations of samples in the minority class in the optimal places. According to the experimental results obtained, the GOS algorithm outperformed other techniques used widely in the imbalanced classification field.
| Item Type: | Conference or Workshop Item (Plenary Papers) |
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| Uncontrolled Keywords: | Imbalanced Classification Re-sampling techniques Quranic Topics Genetic Algorithm |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering |
| Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System |
| Depositing User: | Akram M Zeki |
| Date Deposited: | 12 Sep 2022 14:42 |
| Last Modified: | 12 Sep 2022 14:42 |
| URI: | http://irep.iium.edu.my/id/eprint/99826 |
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