apapiu

# X is the training matrix, y are the labels.
library(xgboost)

n = 100
nrows = dim(X)[1]
nfeats = dim(X)[2]

replicate(n, {
  boot_sample <- sample(1:nrows, replace = TRUE)
  features_selected <- sample(1:nfeats, sqrt(nfeats)) #seems to work better for bagging