# update methods work (eg: linear_reg) Code expr1 %>% update(mixture = 0) Output Linear Regression Model Specification (regression) Main Arguments: mixture = 0 Engine-Specific Arguments: model = FALSE Computational engine: lm --- Code expr1 %>% update(mixture = 0, fresh = TRUE) Output Linear Regression Model Specification (regression) Main Arguments: mixture = 0 Computational engine: lm --- Code expr2 %>% update(nlambda = 10) Output Linear Regression Model Specification (regression) Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr3 %>% update(mixture = 1, nlambda = 10) Output Linear Regression Model Specification (regression) Main Arguments: penalty = tune() mixture = 1 Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr3 %>% update(mixture = 1, nlambda = 10, fresh = TRUE) Output Linear Regression Model Specification (regression) Main Arguments: mixture = 1 Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr3 %>% update(nlambda = 10) Output Linear Regression Model Specification (regression) Main Arguments: penalty = tune() mixture = 0 Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr3 %>% update(nlambda = 10, fresh = TRUE) Output Linear Regression Model Specification (regression) Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr4 %>% update(param_tibb) Output Linear Regression Model Specification (regression) Main Arguments: penalty = 1 mixture = 0.5 Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr4 %>% update(param_list) Output Linear Regression Model Specification (regression) Main Arguments: penalty = 1 mixture = 0.5 Engine-Specific Arguments: nlambda = 10 Computational engine: glmnet --- Code expr4 %>% update(param_tibb, fresh = TRUE) Output Linear Regression Model Specification (regression) Main Arguments: penalty = 1 mixture = 0.5 Computational engine: glmnet --- Code expr4 %>% update(param_list, fresh = TRUE) Output Linear Regression Model Specification (regression) Main Arguments: penalty = 1 mixture = 0.5 Computational engine: glmnet --- Code expr5 %>% update(family = "poisson") Output Linear Regression Model Specification (regression) Engine-Specific Arguments: family = poisson Computational engine: glm --- Code expr5 %>% update(family = "poisson", fresh = TRUE) Output Linear Regression Model Specification (regression) Engine-Specific Arguments: family = poisson Computational engine: glm # update methods prompt informatively Code expr1 %>% update(param_tibb) Condition Error in `update_main_parameters()`: ! At least one argument is not a main argument: `nlambda` --- Code expr1 %>% update(param_list) Condition Error in `update_main_parameters()`: ! At least one argument is not a main argument: `nlambda` --- Code expr1 %>% update(parameters = "wat") Condition Error in `check_final_param()`: ! The parameter object should be a list or tibble --- Code expr1 %>% update(parameters = tibble::tibble(wat = "wat")) Condition Error in `update_main_parameters()`: ! At least one argument is not a main argument: `wat` --- Code linear_reg() %>% update(boop = 0) Condition Error in `update_dot_check()`: ! Extra arguments will be ignored: `boop`