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randomMachines

Installation

You can install the development version of randomMachines from GitHub with:

# install.packages("devtools")
devtools::install_github("MateusMaiaDS/randomMachines")

Example

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)

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Version

Install

install.packages('randomMachines')

Monthly Downloads

257

Version

0.1.1

License

MIT + file LICENSE

Maintainer

Mateus Maia

Last Published

July 23rd, 2025

Functions in randomMachines (0.1.1)

sim_reg3

Simulation for a regression toy examples from Random Machines Regression 3
sim_reg4

Simulation for a regression toy examples from Random Machines Regression 3
rm_reg-class

S4 class for RM regression
predict.rm_reg

Prediction function for the rm_reg_model
brier_score

Brier Score function
bolsafam

Bolsa Família Dataset
RMSE

Root Mean Squared Error (RMSE) Function
rm_class-class

S4 class for RM classification
predict.rm_class

Prediction function for the rm_class_model
sim_class

Generate a binary classification data set from normal distribution
randomMachines

Random Machines
sim_reg5

Simulation for a regression toy examples from Random Machines Regression 3
sim_reg1

Simulation for a regression toy examples from Random Machines Regression 1
sim_reg2

Simulation for a regression toy examples from Random Machines Regression 2
ionosphere

Ionosphere Dataset
whosale

Wholesale Dataset