Supported Models and recipes steps

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Supported models

This table doesn’t exhaustively list fully unsupported models. Please file an issue to add model to table.

Model		Regression	Classification
Supported Prediction Types
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.

Recipes steps

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()

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.