K-means-SMOTE for handling class imbalance in the classification of diabetes with C4.5, SVM, and naive Bayes
The occurrence of imbalanced class in a dataset causes the classification results to tend to the class with the largest amount of data (majority class). A sampling method is needed to balance the minority class (positive class) so that the class distribution becomes balanced and leading to better cl...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Diponegoro University
2020-04-01
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| Series: | Jurnal Teknologi dan Sistem Komputer |
| Subjects: | |
| Online Access: | https://jtsiskom.undip.ac.id/index.php/jtsiskom/article/view/13544 |