Alternative stopping rules to limit tree expansion for random forest models
Abstract Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independent variables. There are relatively few adj...
| Hlavní autoři: | , , |
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| Médium: | Článek |
| Jazyk: | English |
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Nature Portfolio
2022-09-01
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| Edice: | Scientific Reports |
| On-line přístup: | https://doi.org/10.1038/s41598-022-19281-7 |