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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Auteurs principaux: | , , , , |
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Format: | article |
Langue: | EN |
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De Gruyter
2021
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Accès en ligne: | https://doaj.org/article/aa1e6c3d003a415daaa4344d6c9fe55f |
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