# First, set main arguments using the standardized names
logistic_reg(penalty = 0.01, mixture = 1/3) %>%
# Now specify how you want to fit the model with another argument
set_engine("glmnet", nlambda = 10) %>%
translate()
# Many models have possible engine-specific arguments
decision_tree(tree_depth = 5) %>%
set_engine("rpart", parms = list(prior = c(.65,.35))) %>%
set_mode("classification") %>%
translate()
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