Search Results for author:
Found 3 papers, 1 papers with code
Effect of hyperparameters on variable selection in random forests
In conclusion, the default values of the hyperparameters will not always be suitable for identifying important variables.
Evaluation of network-guided random forest for disease gene discovery
Gene network information is believed to be beneficial for disease module and pathway identification, but has not been explicitly utilized in the standard random forest (RF) algorithm for gene expression data analysis.
A review on longitudinal data analysis with random forest in precision medicine
Random forest is one of the state-of-the-art machine learning methods for building prediction models, and can play a crucial role in precision medicine.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
