I want to verify the code to specify a ridge model, a lasso model, and an elastic net model, using parsnip
and glmnet
and the penalty
and mixture
arguments.
I am confused because the documentation states:

mixture
: The proportion of L1 regularization in the model.
and 
mixture
: A number between zero and one (inclusive) that represents the proportion of regularization that is used for the L2 penalty (i.e. weight decay, or ridge regression) versus L1 (the lasso) (glmnet
andspark
only).
So I am not sure if the mixture
represents the proportion of L1 or L2.
 Is this the correct specification for a ridge model?
linear_reg(penalty = .10, mixture = 0) %>% # mixture = 0 meaning no L1 penalty
set_mode("regression") %>%
set_engine("glmnet") %>%
fit(y ~ ., data = dta)
 Is this the correct specification for a lasso model?
linear_reg(penalty = .10, mixture = 1) %>% # mixture = 1 meaning no L2 penalty
set_mode("regression") %>%
set_engine("glmnet") %>%
fit(y ~ ., data = dta)
 Is this the correct specification for an elastic net model?
linear_reg(penalty = .10, mixture = .6) %>% # this is a mixture of both L1 and L2. Is it 60% L1 or 60% L2?
set_mode("regression") %>%
set_engine("glmnet") %>%
fit(y ~ ., data = dta)