rlr_model

0th

Percentile

rlr_model

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

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

# }
Documentation reproduced from package regressoR, version 1.1.7, License: GPL (>= 2)

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