Models

boost_tree()

General Interface for Boosted Trees

decision_tree()

General Interface for Decision Tree Models

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

multinom_reg()

General Interface for Multinomial Regression Models

nearest_neighbor()

General Interface for K-Nearest Neighbor Models

null_model()

General Interface for null models

proportional_hazards()

General Interface for Proportional Hazards Models

rand_forest()

General Interface for Random Forest Models

survival_reg()

General Interface for Parametric Survival Models

svm_linear()

General interface for linear support vector machines

svm_poly()

General interface for polynomial support vector machines

svm_rbf()

General interface for radial basis function support vector machines

Infrastructure

add_rowindex()

Add a column of row numbers to a data frame

augment(<model_fit>)

Augment data with predictions

.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

control_parsnip() fit_control()

Control the fit function

glance(<model_fit>)

Construct a single row summary "glance" of a model, fit, or other object

model_fit

Model Fit Object Information

model_spec

Model Specification Information

multi_predict()

Model predictions across many sub-models

parsnip_addin()

Start an RStudio Addin that can write model specifications

predict(<model_fit>) predict_raw()

Model predictions

repair_call()

Repair a model call object

set_args() set_mode()

Change elements of a model specification

set_engine()

Declare a computational engine and specific arguments

show_engines()

Display currently available engines for a model

tidy(<model_fit>)

Turn a parsnip model object into a tidy tibble

translate()

Resolve a Model Specification for a Computational Engine

update(<boost_tree>) update(<decision_tree>) update(<linear_reg>) update(<logistic_reg>) update(<mars>) update(<mlp>) update(<multinom_reg>) update(<nearest_neighbor>) update(<proportional_hazards>) update(<rand_forest>) update(<surv_reg>) update(<survival_reg>) update(<svm_linear>) update(<svm_poly>) update(<svm_rbf>)

Update a model specification

varying_args(<model_spec>) varying_args(<recipe>) varying_args(<step>)

Determine varying arguments

Developer Tools

contr_one_hot()

Contrast function for one-hot encodings

set_new_model() set_model_mode() set_model_engine() set_model_arg() set_dependency() get_dependency() set_fit() get_fit() set_pred() get_pred_type() show_model_info() pred_value_template() set_encoding() get_encoding()

Tools to Register Models

maybe_matrix() maybe_data_frame()

Fuzzy conversions

min_cols() min_rows()

Execution-time data dimension checks

req_pkgs() required_pkgs(<model_spec>) required_pkgs(<model_fit>)

Determine required packages for a model