Classification of Holy Quran verses based on imbalanced learning
Imbalanced Learning (IL) is considered as a special case of text classification. It is applied in order to classify Imbalanced classes that are not equal in the number of samples. There are many researches on classified Quranic text which depends on different methods of classification. However, th...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
International Journal on Islamic Applications in Computer Science And Technology
2020
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/80764/1/Classification%20of%20Holy%20Quran%20Verse%20based%20on%20Imbalance%20Learning.pdf http://irep.iium.edu.my/80764/ http://www.sign-ific-ance.co.uk/index.php/IJASAT/article/view/2200 |
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| Summary: | Imbalanced Learning (IL) is considered as a special case of text classification. It is applied in order to
classify Imbalanced classes that are not equal in the number of samples. There are many researches on
classified Quranic text which depends on different methods of classification. However, there is no
study that classifies the Quranic topics based on Imbalanced Leaning. So, this paper aims to apply the
concept of IL to assign corresponding topics for the Quranic verses according to their contents. In this
paper, two Quranic datasets have been classified by using Imbalanced Learning consecutively; the
first dataset is Unification of God “Tawheed” and Polytheism of God “Shirk” verses, the second
dataset is Meccan, and Medinan chapters. Imbalanced Classification is applied here since these topics
have imbalanced classes which cannot be classified correctly by traditional methods. The results
showed that applying Imbalanced Classification produces better outcomes than the results that are
executed without using Imbalanced Classification techniques. |
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