List Known Learners
Usage
list_known_learners(
type = c("any", "continuous", "binary", "density", "multiclass")
)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_bart" "lnr_cvglmnet"
#> [3] "lnr_earth" "lnr_gam"
#> [5] "lnr_gausspr" "lnr_gbm"
#> [7] "lnr_glm" "lnr_glm_density"
#> [9] "lnr_glmer" "lnr_glmnet"
#> [11] "lnr_glmnet_grid" "lnr_hal"
#> [13] "lnr_hal_grid" "lnr_heteroskedastic_density"
#> [15] "lnr_homoskedastic_density" "lnr_knn"
#> [17] "lnr_knn_binary" "lnr_lightgbm"
#> [19] "lnr_lm" "lnr_lm_density"
#> [21] "lnr_lmer" "lnr_logistic"
#> [23] "lnr_mean" "lnr_multinomial_nnet"
#> [25] "lnr_multinomial_ranger" "lnr_multinomial_vglm"
#> [27] "lnr_nnet" "lnr_ppr"
#> [29] "lnr_ranger" "lnr_ranger_binary"
#> [31] "lnr_rf" "lnr_rf_binary"
#> [33] "lnr_rpart" "lnr_rpart_binary"
#> [35] "lnr_svm" "lnr_svm_binary"
#> [37] "lnr_xgboost"
list_known_learners("continuous")
#> [1] "lnr_bart" "lnr_cvglmnet" "lnr_earth" "lnr_gam"
#> [5] "lnr_gausspr" "lnr_gbm" "lnr_glm" "lnr_glmer"
#> [9] "lnr_glmnet" "lnr_glmnet_grid" "lnr_hal" "lnr_hal_grid"
#> [13] "lnr_knn" "lnr_lightgbm" "lnr_lm" "lnr_lmer"
#> [17] "lnr_mean" "lnr_ppr" "lnr_ranger" "lnr_rf"
#> [21] "lnr_rpart" "lnr_svm" "lnr_xgboost"
list_known_learners("binary")
#> [1] "lnr_cvglmnet" "lnr_earth" "lnr_gam"
#> [4] "lnr_gbm" "lnr_glm" "lnr_glmer"
#> [7] "lnr_glmnet" "lnr_glmnet_grid" "lnr_hal"
#> [10] "lnr_hal_grid" "lnr_knn_binary" "lnr_lightgbm"
#> [13] "lnr_lm" "lnr_lmer" "lnr_logistic"
#> [16] "lnr_mean" "lnr_nnet" "lnr_ranger"
#> [19] "lnr_ranger_binary" "lnr_rf" "lnr_rf_binary"
#> [22] "lnr_rpart_binary" "lnr_svm_binary" "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_ranger" "lnr_multinomial_vglm"