Improved point center algorithm for K-Means clustering to increase software defect prediction
The k-means is a clustering algorithm that is often and easy to use. This algorithm is susceptible to randomly chosen centroid points so that it cannot produce optimal results. This research aimed to improve the k-means algorithm’s performance by applying a proposed algorithm called point center. Th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Ahmad Dahlan
2020-11-01
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| Series: | IJAIN (International Journal of Advances in Intelligent Informatics) |
| Subjects: | |
| Online Access: | http://ijain.org/index.php/IJAIN/article/view/484 |