The supported methods currently all come from tidypredict right now.
This table doesn’t exhaustively list fully unsupported models. Please file an issue to add model to table.
Supported Prediction Types | ||||
Model
|
Regression
|
Classification
|
||
---|---|---|---|---|
parsnip | engine | numeric | class | prob |
boost_tree() |
"xgboost" |
✅ | ✅ | ✅ |
cubist_rules() |
"Cubist" |
✅ | ❌ | ❌ |
decision_tree() |
"partykit" |
✅ | ✅ | ✅ |
linear_reg() |
"lm" |
✅ | ❌ | ❌ |
linear_reg() |
"glmnet" |
⚪ | ❌ | ❌ |
logistic_reg() |
"glm" |
❌ | ✅ | ✅ |
logistic_reg() |
"glmnet" |
❌ | ⚪ | ⚪ |
mars() |
"earth" |
✅ | ⚪ | ⚪ |
naive_Bayes() |
"naivebayes" |
❌ | ⚪ | ⚪ |
nearest_neighbor() |
any |
❌ | ❌ | ❌ |
rand_forest() |
"randomForest" |
✅ | ⚪ | ⚪ |
rand_forest() |
"ranger" |
✅ | ⚪ | ⚪ |
✅: Supported | ||||
❌: Cannot be supported | ||||
⚪: Not yet supported |
Creating orbital objects of ranger models takes around 1 second per tree. This is in part because the resulting SQL is quite large, making it hard to use on many platforms unless care is taken with regard to hyperparameters and the data.
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()