C5.0_train              Boosted trees via C5.0
boost_tree              General Interface for Boosted Trees
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
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
multi_predict           Model predictions across many sub-models
multinom_reg            General Interface for Multinomial Regression
                        Models
nearest_neighbor        General Interface for K-Nearest Neighbor Models
null_model              General Interface for null models
nullmodel               Fit a simple, non-informative model
predict.model_fit       Model predictions
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
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
varying                 A placeholder function for argument values
varying_args.model_spec
                        Determine varying arguments
wa_churn                Watson Churn Data
xgb_train               Boosted trees via xgboost
