A Common API to Modeling and Analysis Functions


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Documentation for package ‘parsnip’ version 0.0.2

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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
boost_tree General Interface for Boosted Trees
C5.0_train Boosted trees via C5.0
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
fit_xy.model_spec Fit a Model Specification to a Dataset
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
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
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
predict.model_fit Model predictions
predict.nullmodel Fit a simple, non-informative model
print.nullmodel Fit a simple, non-informative model
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
set_mode Change elements of a model specification
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
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
wa_churn Watson Churn Data
xgb_train Boosted trees via xgboost