R: A Common API to Modeling and Analysis Functions

# A Common API to Modeling and Analysis Functions

## Documentation for package ‘parsnip’ version 1.6.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A B C D E F G L M N P R S T U misc

## -- A --

add_rowindex | Add a column of row numbers to a data frame
augment.model_fit | Augment data with predictions
autoplot.glmnet | Create a ggplot for a model object
autoplot.model_fit | Create a ggplot for a model object
auto_ml | Automatic Machine Learning

## -- B --

bag_mars | Ensembles of MARS models
bag_mlp | Ensembles of neural networks
bag_tree | Ensembles of decision trees
bart | Bayesian additive regression trees (BART)
boost_tree | Boosted trees

## -- C --

C5_rules | C5.0 rule-based classification models
case_weights | Using case weights with parsnip
case_weights_allowed | Determine if case weights are used
cforest_train | A wrapper function for conditional inference tree models
control_parsnip | Control the fit function
ctree_train | A wrapper function for conditional inference tree models
cubist_rules | Cubist rule-based regression models

## -- D --

decision_tree | Decision trees
descriptors | Data Set Characteristics Available when Fitting Models
discrim_flexible | Flexible discriminant analysis
discrim_linear | Linear discriminant analysis
discrim_quad | Quadratic discriminant analysis
discrim_regularized | Regularized discriminant analysis

## -- E --

extract-parsnip | Extract elements of a parsnip model object
extract_fit_engine.model_fit | Extract elements of a parsnip model object
extract_fit_time.model_fit | Extract elements of a parsnip model object
extract_parameter_dials.model_spec | Extract elements of a parsnip model object
extract_parameter_set_dials.model_spec | Extract elements of a parsnip model object
extract_spec_parsnip.model_fit | Extract elements of a parsnip model object

## -- F --

fit.model_spec | Fit a Model Specification to a Dataset
fit_xy.model_spec | Fit a Model Specification to a Dataset

## -- G --

gen_additive_mod | Generalized additive models (GAMs)
glance.model_fit | Construct a single row summary "glance" of a model, fit, or other object
glm_grouped | Fit a grouped binomial outcome from a data set with case weights

## -- L --

linear_reg | Linear regression
logistic_reg | Logistic regression

## -- M --

mars | Multivariate adaptive regression splines (MARS)
max_mtry_formula | Determine largest value of mtry from formula. This function potentially caps the value of 'mtry' based on a formula and data set. This is a safe approach for survival and/or multivariate models.
maybe_data_frame | Fuzzy conversions
maybe_matrix | Fuzzy conversions
min_cols | Execution-time data dimension checks
min_rows | Execution-time data dimension checks
mlp | Single layer neural network
model_fit | Model Fit Objects
model_formula | Formulas with special terms in tidymodels
model_spec | Model Specifications
multinom_reg | Multinomial regression
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._glmnetfit | 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._torch_mlp | 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

## -- N --

naive_Bayes | Naive Bayes models
nearest_neighbor | K-nearest neighbors
null_model | Null model

## -- P --

parsnip_addin | Start an RStudio Addin that can write model specifications
parsnip_update | Updating a model specification
pls | Partial least squares (PLS)
poisson_reg | Poisson regression models

## -- R --

rand_forest | Random forest
repair_call | Repair a model call object
required_pkgs.model_fit | Determine required packages for a model
required_pkgs.model_spec | Determine required packages for a model
req_pkgs | Determine required packages for a model
rule_fit | RuleFit models

## -- S --

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
set_mode.model_spec | Change elements of a model specification
show_engines | Display currently available engines for a model
sparse_data | Using sparse data with parsnip
svm_linear | Linear support vector machines
svm_poly | Polynomial support vector machines
svm_rbf | Radial basis function support vector machines

## -- T --

tidy.model_fit | Turn a parsnip model object into a tidy tibble
translate | Resolve a Model Specification for a Computational Engine
translate.default | Resolve a Model Specification for a Computational Engine

## -- U --

update.bag_mars | Updating a model specification
update.bag_mlp | Updating a model specification
update.bag_tree | Updating a model specification
update.bart | Updating a model specification
update.boost_tree | Updating a model specification
update.C5_rules | Updating a model specification
update.cubist_rules | Updating a model specification
update.decision_tree | Updating a model specification
update.discrim_flexible | Updating a model specification
update.discrim_linear | Updating a model specification
update.discrim_quad | Updating a model specification
update.discrim_regularized | Updating a model specification
update.gen_additive_mod | Updating a model specification
update.linear_reg | Updating a model specification
update.logistic_reg | Updating a model specification
update.mars | Updating a model specification
update.mlp | Updating a model specification
update.multinom_reg | Updating a model specification
update.naive_Bayes | Updating a model specification
update.nearest_neighbor | Updating a model specification
update.ordinal_reg | Updating a model specification
update.pls | Updating a model specification
update.poisson_reg | Updating a model specification
update.proportional_hazards | Updating a model specification
update.rand_forest | Updating a model specification
update.rule_fit | Updating a model specification
update.survival_reg | Updating a model specification
update.surv_reg | Updating a model specification
update.svm_linear | Updating a model specification
update.svm_poly | Updating a model specification
update.svm_rbf | Updating a model specification

## -- misc --

.cols | Data Set Characteristics Available when Fitting Models
.dat | Data Set Characteristics Available when Fitting Models
.extract_surv_status | Extract survival status
.extract_surv_time | Extract survival time
.facts | Data Set Characteristics Available when Fitting Models
.get_prediction_column_names | Obtain names of prediction columns for a fitted model or workflow
.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