A Common API to Modeling and Analysis Functions


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Documentation for package ‘parsnip’ version 0.1.5

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.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
add_rowindex Add a column of row numbers to a data frame
augment.model_fit Augment data with predictions
boost_tree General Interface for Boosted Trees
control_parsnip Control the fit function
contr_one_hot Contrast function for one-hot encodings
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
glance.model_fit Construct a single row summary "glance" of a model, fit, or other object
linear_reg General Interface for Linear Regression Models
logistic_reg General Interface for Logistic Regression Models
mars General Interface for MARS
maybe_data_frame Fuzzy conversions
maybe_matrix Fuzzy conversions
min_cols Execution-time data dimension checks
min_rows Execution-time data dimension checks
mlp General Interface for Single Layer Neural Network
model_db parsnip model specification database
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
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._lognet Model predictions across many sub-models
multi_predict._multnet 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
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
parsnip_addin Start an RStudio Addin that can write model specifications
predict.nullmodel Fit a simple, non-informative model
print.nullmodel Fit a simple, non-informative model
rand_forest General Interface for Random Forest Models
repair_call Repair a model call object
req_pkgs Determine required packages for a model
req_pkgs.model_fit Determine required packages for a model
req_pkgs.model_spec Determine required packages for a model
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
show_engines Display currently available engines for a model
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
tidy.nullmodel Tidy method for null models
tidy._elnet tidy methods for glmnet models
tidy._fishnet tidy methods for glmnet models
tidy._lognet tidy methods for glmnet models
tidy._multnet tidy methods for glmnet models
translate Resolve a Model Specification for a Computational Engine
translate.default 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