| .cols | Data Set Characteristics Available when Fitting Models |
| .dat | Data Set Characteristics Available when Fitting Models |
| .facts | Data Set Characteristics Available when Fitting Models |
| .lvls | Data Set Characteristics Available when Fitting Models |
| .obs | Data Set Characteristics Available when Fitting Models |
| .preds | Data Set Characteristics Available when Fitting Models |
| .x | Data Set Characteristics Available when Fitting Models |
| .y | Data Set Characteristics Available when Fitting Models |
| add_rowindex | Add a column of row numbers to a data frame |
| boost_tree | General Interface for Boosted Trees |
| control_parsnip | Control the fit function |
| contr_one_hot | Contrast function for one-hot encodings |
| decision_tree | General Interface for Decision Tree Models |
| descriptors | Data Set Characteristics Available when Fitting Models |
| fit.model_spec | Fit a Model Specification to a Dataset |
| fit_control | Control the fit function |
| fit_xy.model_spec | Fit a Model Specification to a Dataset |
| linear_reg | General Interface for Linear Regression Models |
| logistic_reg | General Interface for Logistic Regression Models |
| mars | General Interface for MARS |
| mlp | General Interface for Single Layer Neural Network |
| model_fit | Model Fit Object Information |
| model_spec | Model Specification Information |
| multinom_reg | General Interface for Multinomial Regression Models |
| multi_predict | Model predictions across many sub-models |
| multi_predict.default | Model predictions across many sub-models |
| multi_predict._C5.0 | Model predictions across many sub-models |
| multi_predict._earth | Model predictions across many sub-models |
| multi_predict._elnet | Model predictions across many sub-models |
| multi_predict._lognet | Model predictions across many sub-models |
| multi_predict._multnet | Model predictions across many sub-models |
| multi_predict._train.kknn | Model predictions across many sub-models |
| multi_predict._xgb.Booster | Model predictions across many sub-models |
| nearest_neighbor | General Interface for K-Nearest Neighbor Models |
| nullmodel | Fit a simple, non-informative model |
| nullmodel.default | Fit a simple, non-informative model |
| null_model | General Interface for null models |
| predict.nullmodel | Fit a simple, non-informative model |
| print.nullmodel | Fit a simple, non-informative model |
| rand_forest | General Interface for Random Forest Models |
| repair_call | Repair a model call object |
| req_pkgs | Determine required packages for a model |
| req_pkgs.model_fit | Determine required packages for a model |
| req_pkgs.model_spec | Determine required packages for a model |
| set_args | Change elements of a model specification |
| set_engine | Declare a computational engine and specific arguments |
| set_mode | Change elements of a model specification |
| surv_reg | General Interface for Parametric Survival Models |
| svm_poly | General interface for polynomial support vector machines |
| svm_rbf | General interface for radial basis function support vector machines |
| tidy.model_fit | Turn a parsnip model object into a tidy tibble |
| tidy.nullmodel | Tidy method for null models |
| translate | Resolve a Model Specification for a Computational Engine |
| translate.default | Resolve a Model Specification for a Computational Engine |
| update.boost_tree | General Interface for Boosted Trees |
| update.decision_tree | General Interface for Decision Tree Models |
| update.linear_reg | General Interface for Linear Regression Models |
| update.logistic_reg | General Interface for Logistic Regression Models |
| update.mars | General Interface for MARS |
| update.mlp | General Interface for Single Layer Neural Network |
| update.multinom_reg | General Interface for Multinomial Regression Models |
| update.rand_forest | General Interface for Random Forest Models |
| update.surv_reg | General Interface for Parametric Survival Models |
| update.svm_poly | General interface for polynomial support vector machines |
| update.svm_rbf | General interface for radial basis function support vector machines |
| varying | A placeholder function for argument values |
| varying_args.model_spec | Determine varying arguments |
| varying_args.recipe | Determine varying arguments |
| varying_args.step | Determine varying arguments |