Models

boost_tree() update(<boost_tree>)

General Interface for Boosted Trees

decision_tree() update(<decision_tree>)

General Interface for Decision Tree Models

linear_reg() update(<linear_reg>)

General Interface for Linear Regression Models

logistic_reg() update(<logistic_reg>)

General Interface for Logistic Regression Models

mars() update(<mars>)

General Interface for MARS

mlp() update(<mlp>)

General Interface for Single Layer Neural Network

multinom_reg() update(<multinom_reg>)

General Interface for Multinomial Regression Models

nearest_neighbor()

General Interface for K-Nearest Neighbor Models

null_model()

General Interface for null models

rand_forest() update(<rand_forest>)

General Interface for Random Forest Models

surv_reg() update(<surv_reg>)

General Interface for Parametric Survival Models

svm_poly() update(<svm_poly>)

General interface for polynomial support vector machines

svm_rbf() update(<svm_rbf>)

General interface for radial basis function support vector machines

Infrastructure

.cols() .preds() .obs() .lvls() .facts() .x() .y() .dat()

Data Set Characteristics Available when Fitting Models

fit(<model_spec>) fit_xy(<model_spec>)

Fit a Model Specification to a Dataset

reexports

Objects exported from other packages

fit_control()

Control the fit function

model_fit

Model Fit Object Information

model_spec

Model Specification Information

predict(<model_fit>)

Model predictions

multi_predict()

Model predictions across many sub-models

set_args() set_mode()

Change elements of a model specification

set_engine()

Declare a computational engine and specific arguments

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

Data

lending_club

Loan Data

wa_churn

Watson Churn Data

check_times

Execution Time Data