Knowledge-slanted random forest method for high-dimensional data and small sample size with a feature selection application for gene expression data
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1186/s13040-024-00388-8.pdf
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5. Speiser JL, Miller ME, Tooze J, Ip E. A comparison of random forest variable selection methods for classification prediction modeling. Expert Syst Appl. 2019;134:93–101.
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