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Utility Regression call to parsnip

Source: R/utils-reg-to-parsnip.R
fast_regression_parsnip_spec_tbl.Rd

Creates a tibble of parsnip regression model specifications.

Usage

fast_regression_parsnip_spec_tbl(.parsnip_fns = "all", .parsnip_eng = "all")

Arguments

.parsnip_fns

The default for this is set to all. This means that all of the parsnip linear regression functions will be used, for example linear_reg(), or cubist_rules. You can also choose to pass a c() vector like c("linear_reg","cubist_rules")

.parsnip_eng

The default for this is set to all. This means that all of the parsnip linear regression engines will be used, for example lm, or glm. You can also choose to pass a c() vector like c('lm', 'glm')

Value

A tibble with an added class of 'fst_reg_spec_tbl'

Details

Creates a tibble of parsnip regression model specifications. This will create a tibble of 46 different regression model specifications which can be filtered. The model specs are created first and then filtered out. This will only create models for regression problems. To find all of the supported models in this package you can visit https://www.tidymodels.org/find/parsnip/

See also

Other Utility: core_packages(), create_splits(), create_workflow_set(), fast_classification_parsnip_spec_tbl(), full_internal_make_wflw(), install_deps(), load_deps(), match_args()

Author

Steven P. Sanderson II, MPH

Examples

fast_regression_parsnip_spec_tbl(.parsnip_fns = "linear_reg")
#> # A tibble: 11 × 5
#>    .model_id .parsnip_engine .parsnip_mode .parsnip_fns model_spec
#>        <int> <chr>           <chr>         <chr>        <list>    
#>  1         1 lm              regression    linear_reg   <spec[+]> 
#>  2         2 brulee          regression    linear_reg   <spec[+]> 
#>  3         3 gee             regression    linear_reg   <spec[+]> 
#>  4         4 glm             regression    linear_reg   <spec[+]> 
#>  5         5 glmer           regression    linear_reg   <spec[+]> 
#>  6         6 glmnet          regression    linear_reg   <spec[+]> 
#>  7         7 gls             regression    linear_reg   <spec[+]> 
#>  8         8 lme             regression    linear_reg   <spec[+]> 
#>  9         9 lmer            regression    linear_reg   <spec[+]> 
#> 10        10 stan            regression    linear_reg   <spec[+]> 
#> 11        11 stan_glmer      regression    linear_reg   <spec[+]> 
fast_regression_parsnip_spec_tbl(.parsnip_eng = c("lm","glm"))
#> # A tibble: 3 × 5
#>   .model_id .parsnip_engine .parsnip_mode .parsnip_fns model_spec
#>       <int> <chr>           <chr>         <chr>        <list>    
#> 1         1 lm              regression    linear_reg   <spec[+]> 
#> 2         2 glm             regression    linear_reg   <spec[+]> 
#> 3         3 glm             regression    poisson_reg  <spec[+]>