A numeric parameter function representing the relative amount of penalties (e.g. L1, L2, etc) in regularized models.

## Usage

`mixture(range = c(0, 1), trans = NULL)`

## Arguments

- range
A two-element vector holding the

*defaults*for the smallest and largest possible values, respectively. If a transformation is specified, these values should be in the*transformed units*.- trans
A

`trans`

object from the`scales`

package, such as`scales::transform_log10()`

or`scales::transform_reciprocal()`

. If not provided, the default is used which matches the units used in`range`

. If no transformation,`NULL`

.

## Details

This parameter is used for regularized or penalized models such as
`parsnip::linear_reg()`

, `parsnip::logistic_reg()`

, and others. It is
formulated as the proportion of L1 regularization (i.e. lasso) in the model.
In the `glmnet`

model, `mixture = 1`

is a pure lasso model while `mixture = 0`

indicates that ridge regression is being used.