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Regularized impurity reduction: accurate decision trees with complexity guarantees
Decision trees are popular classification models, providing high accuracy and intuitive explanations. However, as the tree size grows the model interpretability deteriorates. Traditional tree-induction algorithms, such as C4.5 and CART, rely on impurity-reduction functions that promote the discrimin...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813065/ https://www.ncbi.nlm.nih.gov/pubmed/36618773 http://dx.doi.org/10.1007/s10618-022-00884-7 |