regressoR (version 1.1.8)

rlr_model: rlr_model

Description

generates the code to create the penalized regression model.

Usage

rlr_model(data = "datos.aprendizaje", variable.pred = NULL,
  model.var = "modelo.rlr", cv.var = "cv.glm", alpha = 0,
  standardize = TRUE)

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.

cv.var

the variable that stores the optimal lambda.

alpha

the alpha parameter of the model.

standardize

the standardize parameter of the model.

See Also

glmnet, cv.glmnet

Examples

# NOT RUN {
library(glmnet)
x <- rlr_model('iris', 'Petal.Length')
exe(x)
print(modelo.rlr)

# }