The supported models currently all come from tidypredict right now.
The following models are supported by tidypredict
:
lm()
glm()
randomForest::randomForest()
ranger
-
ranger::ranger()
earth::earth()
xgboost::xgb.Booster.complete()
Cubist::cubist()
partykit
-
partykit::ctree()
parsnip
tidypredict
supports models fitted via the
parsnip
interface. The ones confirmed currently work in
tidypredict
are:
lm()
- parsnip
: linear_reg()
with “lm” as the engine.randomForest::randomForest()
- parsnip
:
rand_forest()
with “randomForest” as the
engine.ranger::ranger()
- parsnip
:
rand_forest()
with “ranger” as the engine.earth::earth()
- parsnip
:
mars()
with “earth” as the engine.The following 46 recipes steps are supported
step_BoxCox()
step_adasyn()
step_bin2factor()
step_bsmote()
step_center()
step_corr()
step_discretize()
step_downsample()
step_dummy()
step_filter_missing()
step_impute_mean()
step_impute_median()
step_impute_mode()
step_indicate_na()
step_intercept()
step_inverse()
step_lag()
step_lencode_bayes()
step_lencode_glm()
step_lencode_mixed()
step_lincomb()
step_log()
step_mutate()
step_nearmiss()
step_normalize()
step_novel()
step_nzv()
step_other()
step_pca()
step_pca_sparse()
step_pca_sparse_bayes()
step_pca_truncated()
step_range()
step_ratio()
step_rename()
step_rm()
step_rose()
step_scale()
step_select()
step_smote()
step_smotenc()
step_sqrt()
step_tomek()
step_unknown()
step_upsample()
step_zv()