List Known Learners

Usage

list_known_learners(type = "any")

Arguments

type: One of 'any' or a supported outcome type in nadir including at least 'continuous', 'binary', 'multiclass', 'density'. See ?super_learner().

Value

A character vector of functions that were automatically recognized as nadir learners with the prediction/outcome type given.

Examples

list_known_learners()
#>  [1] "lnr_earth"                   "lnr_gam"                    
#>  [3] "lnr_glm"                     "lnr_glm_density"            
#>  [5] "lnr_glmer"                   "lnr_glmnet"                 
#>  [7] "lnr_heteroskedastic_density" "lnr_homoskedastic_density"  
#>  [9] "lnr_lm"                      "lnr_lm_density"             
#> [11] "lnr_lmer"                    "lnr_logistic"               
#> [13] "lnr_mean"                    "lnr_multinomial_nnet"       
#> [15] "lnr_multinomial_vglm"        "lnr_nnet"                   
#> [17] "lnr_ranger"                  "lnr_rf"                     
#> [19] "lnr_rf_binary"               "lnr_xgboost"                
list_known_learners('continuous')
#>  [1] "lnr_earth"   "lnr_gam"     "lnr_glm"     "lnr_glmer"   "lnr_glmnet" 
#>  [6] "lnr_lm"      "lnr_lmer"    "lnr_mean"    "lnr_ranger"  "lnr_rf"     
#> [11] "lnr_xgboost"
list_known_learners('binary')
#>  [1] "lnr_earth"     "lnr_gam"       "lnr_glm"       "lnr_glmer"    
#>  [5] "lnr_glmnet"    "lnr_lm"        "lnr_lmer"      "lnr_logistic" 
#>  [9] "lnr_mean"      "lnr_nnet"      "lnr_ranger"    "lnr_rf_binary"
#> [13] "lnr_xgboost"  
list_known_learners('density')
#> [1] "lnr_glm_density"             "lnr_heteroskedastic_density"
#> [3] "lnr_homoskedastic_density"   "lnr_lm_density"             
list_known_learners('multiclass')
#> [1] "lnr_multinomial_nnet" "lnr_multinomial_vglm"