Instance Reduction for Avoiding Overfitting in Decision Trees
Decision trees learning is one of the most practical classification methods in machine learning, which is used for approximating discrete-valued target functions. However, they may overfit the training data, which limits their ability to generalize to unseen instances. In this study, we investigated...
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| Автори: | , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
De Gruyter
2021-01-01
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| Серія: | Journal of Intelligent Systems |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1515/jisys-2020-0061 |
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