Confidence evaluation for feature selection in expanded feature space based on density of states
In materials informatics, feature selection and model selection are utilized in the knowledge extraction process, and the confidence evaluation of the selection result is crucial for ensuring the reliability of the extracted knowledge. In this study, we propose a novel method to quantitatively evalu...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-03-01
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| Series: | APL Machine Learning |
| Online Access: | http://dx.doi.org/10.1063/5.0245626 |
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