Feature representation via graph-regularized entropy-weighted nonnegative matrix factorization
Feature extraction plays a crucial role in dimensionality reduction in machine learning applications. Nonnegative Matrix Factorization (NMF) has emerged as a powerful technique for dimensionality reduction; however, its equal treatment of all features may limit accuracy. To address this challenge, t...
| Asıl Yazarlar: | , , |
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| Materyal Türü: | Makale |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
Amirkabir University of Technology
2024-10-01
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| Seri Bilgileri: | AUT Journal of Mathematics and Computing |
| Konular: | |
| Online Erişim: | https://ajmc.aut.ac.ir/article_5535_3112c9212ca8838f81402e7dd4358c84.pdf |