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Interpretation of Machine Learning Models for Data Sets with Many Features Using Feature Importance
[Image: see text] Feature importance (FI) is used to interpret the machine learning model y = f(x) constructed between the explanatory variables or features, x, and the objective variables, y. For a large number of features, interpreting the model in the order of increasing FI is inefficient when th...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Chemical Society
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308517/ https://www.ncbi.nlm.nih.gov/pubmed/37396269 http://dx.doi.org/10.1021/acsomega.3c03722 |