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generates the code to print the penalized regression coefficients.
coef_lambda(data = "datos.aprendizaje", variable.pred = NULL, model.var = "modelo.rlr", lambda = NULL, cv.var = "cv.glm")
the name of the learning data.
the name of the variable to be predicted.
the name of the variable that stores the resulting model.
a numerical value in case you don't want to use the optimal lambda.
the variable that stores the optimal lambda.
# NOT RUN { library(glmnet) x <- rlr_model('iris', 'Petal.Length') exe(x) x <- coef_lambda('iris','Petal.Length', 'modelo.rlr') exe(x) # }
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