.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 |
boost_tree | General Interface for Boosted Trees |
C5.0_train | Boosted trees via C5.0 |
check_times | Execution Time Data |
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 |
keras_mlp | Simple interface to MLP models via keras |
lending_club | Loan Data |
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 |
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.model_fit | Model predictions |
predict.nullmodel | Fit a simple, non-informative model |
print.nullmodel | Fit a simple, non-informative model |
rand_forest | General Interface for Random Forest Models |
rpart_train | Decision trees via rpart |
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 |
translate | 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 |
wa_churn | Watson Churn Data |
xgb_train | Boosted trees via xgboost |