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

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

Arguments

range

A two-element vector holding the defaults for the smallest and largest possible values, respectively.

trans

A trans object from the scales package, such as scales::log10_trans() or scales::reciprocal_trans(). 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.

Examples

mixture()
#> Proportion of lasso Penalty (quantitative) #> Range: [0, 1]