Learning from High-Dimensional and Class-Imbalanced Datasets Using Random Forests
Class imbalance and high dimensionality are two major issues in several real-life applications, e.g., in the fields of bioinformatics, text mining and image classification. However, while both issues have been extensively studied in the machine learning community, they have mostly been treated separ...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Information |
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| Online Access: | https://www.mdpi.com/2078-2489/12/8/286 |