randomForestSRC
Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
Fast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. New Mahalanobis splitting for correlated outcomes. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and standard errors for variable importance. New improved holdout importance. Case-specific importance. Minimal depth variable importance. Visualize trees on your Safari or Google Chrome browser. Anonymous random forests for data privacy.
- https://www.randomforestsrc.org/
- https://ishwaran.org/
- File a bug report
- randomForestSRC results
- randomForestSRC.pdf
- Version3.3.1
- R version≥ 4.3.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- randomForestSRC citation info
- Last release07/25/2024
Documentation
Team
Udaya B. Kogalur
Hemant Ishwaran, Udaya B. Kogalur
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Dependencies
- Depends1 package
- Imports3 packages
- Suggests10 packages
- Reverse Depends1 package
- Reverse Imports12 packages
- Reverse Suggests10 packages
- Reverse Enhances1 package