Regularized K-Means Clustering via Fully Corrective Frank-Wolfe Optimization
Clustering high-dimensional data remains challenging because traditional k-means is sensitive to noise, outliers, and high dimensionality, often leading to unstable performance. The research presents a robust clustering system which combines the Fully Corrective Frank-Wolfe (FCFW) algorithm with k-...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad
2025-08-01
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| Series: | Journal of Engineering |
| Subjects: | |
| Online Access: | https://joe.uobaghdad.edu.iq/index.php/main/article/view/3680 |
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