🔴 This package is deprecated. Please use one of the following packages instead: 🔴
- grf, which has built-in support for resampling-based confidence intervals, or
- ranger, which has an actively maintained version of the infinitesimal jackknife for random forests.
🔴 Both packages are available from CRAN. 🔴
Confidence intervals for random forests using the infinitesimal jackknife, as developed by Efron (2014) and Wager et al. (2014).
To install this package in R, run the following commands:
install.packages("devtools")
library(devtools)
install_github("swager/randomForestCI")
Example usage:
library(randomForestCI)
# Make some data...
n = 250
p = 100
X = matrix(rnorm(n * p), n, p)
Y = rnorm(n)
# Run the method
rf = randomForest(X, Y, keep.inbag = TRUE)
ij = randomForestInfJack(rf, X, calibrate = TRUE)
plot(ij)
Efron, Bradley. Estimation and accuracy after model selection. Journal of the American Statistical Association, 109(507), 2014. [link]
Wager, Stefan, Trevor Hastie, and Bradley Efron. Confidence intervals for random forests: The jackknife and the infinitesimal jackknife. The Journal of Machine Learning Research, 15(1), 2014. [link]