Mixture of penalization termsSource:
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)
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.
transobject from the
scalespackage, such as
scales::reciprocal_trans(). If not provided, the default is used which matches the units used in
range. If no transformation,
This parameter is used for regularized or penalized models such as
parsnip::logistic_reg(), and others. It is
formulated as the proportion of L1 regularization (i.e. lasso) in the model.
mixture = 1 is a pure lasso model while
mixture = 0
indicates that ridge regression is being used.