Critical evaluation of feature importance assessment in FFNN-based models for predicting Kamlet-Taft parameters
Mohan et al. developed a feed-forward neural network (FFNN) model to predict Kamlet-Taft parameters using quantum chemically derived features, achieving notable predictive accuracy. However, this study raises concerns about conflating prediction accuracy with feature importance accuracy, as high R2...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2025-09-01
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| Series: | Green Chemical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666952825000032 |
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