Make create_model_spec() function

[spsanderson]

The purpose

The purpose of this function is to allow a user to create a model specification of any parsnip type or multiples of different types. It can return either a list of the model specifications or a tibble both of which have the same information.

Function:

library(purrr)
library(parsnip)

create_model_spec <- function(.parsnip_engine = list("lm"), 
                              .mode = list("regression"),
                              .parsnip_fns = list("linear_reg"),
                              .return_tibble = TRUE) {
  
  # Tidyeval ----
  engine <- .parsnip_engine %>%
    purrr::flatten_chr() %>%
    as.list()
  mode <- .mode %>%
    purrr::flatten_chr() %>%
    as.list()
  call <- .parsnip_fns %>%
    purrr::flatten_chr() %>%
    as.list()
  ret_tibble <- as.logical(.return_tibble)

  # Make Model list for purrr call
  model_spec_list <- list(
    call,
    engine,
    mode
  )

  # Use purrr pmap to make mode specs
  models <- purrr::pmap(
    .l = model_spec_list,
    .f = function(call, engine, mode) {
      match.fun(call)(engine = engine, mode = mode)
    }
  )

  # Return ----
  models_list <- list(
    .parsnip_engine = engine,
    .parsnip_mode = mode,
    .parsnip_fns = call,
    .model_spec = models
  )

  ret_tbl <- dplyr::tibble(
    .parsnip_engine = unlist(engine),
    .parsnip_mode   = unlist(mode),
    .parsnip_fns    = unlist(call),
    .model_spec     = models
  )

  ifelse(ret_tibble, return(ret_tbl), return(models_list))
}

Examples:

> create_model_spec(
+   .engine = list("lm","glm","glmnet","cubist"), 
+   .parsnip_fns = list(
+     rep("linear_reg", 3),
+     "cubist_rules")
+   )
# A tibble: 4 × 4
  .parsnip_engine .parsnip_mode .parsnip_fns .model_spec
  <chr>           <chr>         <chr>        <list>     
1 lm              regression    linear_reg   <spec[+]>  
2 glm             regression    linear_reg   <spec[+]>  
3 glmnet          regression    linear_reg   <spec[+]>  
4 cubist          regression    cubist_rules <spec[+]>  
> model_spec_list <- create_model_spec(
+   .engine = list("lm","glm","glmnet","cubist"), 
+   .parsnip_fns = list(
+     rep("linear_reg", 3),
+     "cubist_rules"),
+   .return_tibble = FALSE
+ )
> model_spec_list$.model_spec
[[1]]
Linear Regression Model Specification (regression)

Computational engine: lm 


[[2]]
Linear Regression Model Specification (regression)

Computational engine: glm 


[[3]]
Linear Regression Model Specification (regression)

Computational engine: glmnet 


[[4]]
! parsnip could not locate an implementation for `cubist_rules` regression model
  specifications using the `cubist` engine.

Cubist Model Specification (regression)

Computational engine: cubist