You can install the development version of randomMachines from GitHub with:
# install.packages("devtools")
# devtools::install_github("MateusMaiaDS/randomMachines")
install.packages("randomMachines", repos = c('https://mateusmaiads.r-universe.dev', 'https://cloud.r-project.org'))
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
library(randomMachines)
## Simple regression example
sim_train <- randomMachines::sim_reg1(n=100)
sim_test <- randomMachines::sim_reg1(n=100)
rm_mod <- randomMachines::randomMachines(y~.,train = sim_train,B = 25)
rm_mod_pred <- predict(rm_mod,sim_test)