r descr_models("linear_reg", "keras")
defaults <- tibble::tibble(parsnip = c("penalty"), default = c("0.0")) param <- linear_reg() %>% set_engine("keras") %>% make_parameter_list(defaults)
This model has one tuning parameter:
param$item
For penalty
, the amount of regularization is only L2 penalty (i.e., ridge or weight decay).
linear_reg(penalty = double(1)) %>% set_engine("keras") %>% translate()
[keras_mlp()] is a parsnip wrapper around keras code for neural networks. This model fits a linear regression as a network with a single hidden unit.
The "Fitting and Predicting with parsnip" article contains examples for linear_reg()
with the "keras"
engine.
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