You can install the development version of randomMachines from GitHub with:
This is a basic example which shows you how to solve a common binary classification problem:
library(randomMachines)
## Simple classification example
sim_train <- randomMachines::sim_class(n=100)
sim_test <- randomMachines::sim_class(n=100)
rm_mod <- randomMachines::randomMachines(y~.,train = sim_train, B = 25,prob_model = F)
rm_mod_pred <- predict(rm_mod,sim_test)
For a regression task we would have similarly