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parsnip (version 0.1.4)

A Common API to Modeling and Analysis Functions

Description

A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', etc).

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Install

install.packages('parsnip')

Monthly Downloads

49,201

Version

0.1.4

License

GPL-2

Issues

86

Pull Requests

3

Stars

618

Forks

91

Maintainer

Max Kuhn

Last Published

October 27th, 2020

Functions in parsnip (0.1.4)

null_value

Functions required for parsnip-adjacent packages
decision_tree

General Interface for Decision Tree Models
add_rowindex

Add a column of row numbers to a data frame
contr_one_hot

Contrast function for one-hot encodings
descriptors

Data Set Characteristics Available when Fitting Models
convert_stan_interval

Convenience function for intervals
C5.0_train

Boosted trees via C5.0
check_empty_ellipse

Check to ensure that ellipses are empty
control_parsnip

Control the fit function
boost_tree

General Interface for Boosted Trees
linear_reg

General Interface for Linear Regression Models
make_call

Make a parsnip call expression
min_cols

Execution-time data dimension checks
req_pkgs

Determine required packages for a model
mlp

General Interface for Single Layer Neural Network
rpart_train

Decision trees via rpart
model_printer

Print helper for model objects
repair_call

Repair a model call object
model_fit

Model Fit Object Information
keras_mlp

Simple interface to MLP models via keras
has_multi_predict

Tools for models that predict on sub-models
tidy._elnet

tidy methods for glmnet models
fit.model_spec

Fit a Model Specification to a Dataset
eval_args

Evaluate parsnip model arguments
get_model_env

Working with the parsnip model environment
reexports

Objects exported from other packages
logistic_reg

General Interface for Logistic Regression Models
make_classes

Prepend a new class
tidy.model_fit

Turn a parsnip model object into a tidy tibble
multinom_reg

General Interface for Multinomial Regression Models
mars

General Interface for MARS
glance.model_fit

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

Display currently available engines for a model
surv_reg

General Interface for Parametric Survival Models
nearest_neighbor

General Interface for K-Nearest Neighbor Models
null_model

General Interface for null models
model_spec

Model Specification Information
multi_predict

Model predictions across many sub-models
maybe_matrix

Fuzzy conversions
prepare_data

Prepare data based on parsnip encoding information
set_args

Change elements of a model specification
predict_class.model_fit

Other predict methods.
predict.model_fit

Model predictions
set_engine

Declare a computational engine and specific arguments
set_new_model

Tools to Register Models
nullmodel

Fit a simple, non-informative model
type_sum.model_spec

Succinct summary of parsnip object
rand_forest

General Interface for Random Forest Models
varying

A placeholder function for argument values
varying_args.model_spec

Determine varying arguments
xgb_train

Boosted trees via xgboost
show_call

Print the model call
svm_poly

General interface for polynomial support vector machines
translate

Resolve a Model Specification for a Computational Engine
tidy.nullmodel

Tidy method for null models
svm_rbf

General interface for radial basis function support vector machines