Enhancing agricultural data interpretability and visualization with TabNet-driven feature extraction and Local Biplots
Modern agriculture faces escalating challenges that demand predictive models balancing accuracy and interpretability to support informed decision-making. While precision agriculture has advanced through high-resolution remote sensing technologies capturing spectral, thermal, and soil data, interpret...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025027392 |
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