regressoR (version 1.1.7)

rf_model: rf_model

Description

generates the code to create the random forest model.

Usage

rf_model(data = "datos.aprendizaje", variable.pred = NULL,
  model.var = "modelo.rf", ntree = 500, mtry = 1)

Arguments

data

the name of the learning data.

variable.pred

the name of the variable to be predicted.

model.var

the name of the variable that stores the resulting model.

ntree

the ntree parameter of the model.

mtry

the mtry parameter of the model.

See Also

randomForest

Examples

# NOT RUN {
library(randomForest)
x <- rf_model('iris', 'Petal.Length')
exe(x)
print(modelo.rf)

# }