Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection
Gradient Boosting Machines (GBM) are among the go-to algorithms on tabular data, which produce state-of-the-art results in many prediction tasks. Despite its popularity, the GBM framework suffers from a fundamental flaw in its base learners. Specifically, most implementations utilize decision trees...
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| Principais autores: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
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MDPI AG
2022-05-01
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| coleção: | Entropy |
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| Acesso em linha: | https://www.mdpi.com/1099-4300/24/5/687 |
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