cla_glmnet: LASSO logistic regression (glmnet)

In daltoolbox: Leveraging Experiment Lines to Data Analytics

LASSO logistic regression (glmnet)

Description

Logistic regression with L1 penalty using glmnet::cv.glmnet.

Usage

cla_glmnet(attribute, lambda = c("lambda.min", "lambda.1se"))

Arguments

attribute	target attribute name (binary)
lambda	which lambda to use ("lambda.min" or "lambda.1se")

Value

returns a cla_glmnet object

Examples

if (requireNamespace("glmnet", quietly = TRUE)) {
 data(iris)
 iris_bin <- iris
 iris_bin$IsVersicolor <- ifelse(iris_bin$Species == "versicolor", 1, 0)
 model <- cla_glmnet("IsVersicolor")
 model <- fit(model, iris_bin)
 pred <- predict(model, iris_bin)
 table(pred, iris_bin$IsVersicolor)
}

daltoolbox documentation built on Feb. 10, 2026, 9:06 a.m.