Functions required for parsnip-adjacent packages
Contrast function for one-hot encodings
General Interface for Decision Tree Models
General Interface for Boosted Trees
Tools for models that predict on sub-models
Working with the parsnip model environment
General Interface for Logistic Regression Models
General Interface for Single Layer Neural Network
General Interface for Linear Regression Models
General Interface for MARS
Model Specification Information
Other predict methods.
Simple interface to MLP models via keras
Prepend a new class
Model Fit Object Information
General Interface for Multinomial Regression Models
General Interface for null models
Model predictions across many sub-models
Fit a simple, non-informative model
Model predictions
Declare a computational engine and specific arguments
Repair a model call object
Decision trees via rpart
Tools to Register Models
General Interface for Parametric Survival Models
General interface for radial basis function support vector machines
Evaluate parsnip model arguments
Print helper for model objects
General interface for polynomial support vector machines
General Interface for K-Nearest Neighbor Models
Change elements of a model specification
Print the model call
Turn a parsnip model object into a tidy tibble
Determine required packages for a model
Tidy method for null models
Succinct summary of parsnip object
Resolve a Model Specification for a Computational Engine
Fit a Model Specification to a Dataset
Boosted trees via xgboost
A placeholder function for argument values
Determine varying arguments
General Interface for Random Forest Models
Objects exported from other packages
Boosted trees via C5.0
Add a column of row numbers to a data frame
Control the fit function
Data Set Characteristics Available when Fitting Models
Convenience function for intervals
Check to ensure that ellipses are empty