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parsnip (version 0.1.6)

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

0.1.6

License

MIT + file LICENSE

Issues

Pull Requests

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Repository

https://github.com/tidymodels/parsnip

Homepage

https://parsnip.tidymodels.org

Maintainer

Max Kuhn

Last Published

May 27th, 2021

Functions in parsnip (0.1.6)

Add a column of row numbers to a data frame

Boosted trees via C5.0

Contrast function for one-hot encodings

convert_stan_interval

Convenience function for intervals

control_parsnip

Control the fit function

Functions required for parsnip-adjacent packages

General Interface for Boosted Trees

check_empty_ellipse

Check to ensure that ellipses are empty

General Interface for Logistic Regression Models

augment.model_fit

Augment data with predictions

Make a parsnip call expression

Fit a Model Specification to a Dataset

Working with the parsnip model environment

Data Set Characteristics Available when Fitting Models

Evaluate parsnip model arguments

General Interface for Decision Tree Models

General Interface for Single Layer Neural Network

General Interface for Linear Regression Models

Simple interface to MLP models via keras

Model predictions across many sub-models

Model Specification Information

parsnip model specification database

Prepend a new class

General Interface for MARS

Start an RStudio Addin that can write model specifications

predict_class.model_fit

Other predict methods.

Fuzzy conversions

update.boost_tree

Update a model specification

glance.model_fit

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

Model Fit Object Information

Print helper for model objects

predict.model_fit

Model predictions

Execution-time data dimension checks

Prepare data based on parsnip encoding information

General Interface for Random Forest Models

proportional_hazards

General Interface for Proportional Hazards Models

has_multi_predict

Tools for models that predict on sub-models

General Interface for null models

Fit a simple, non-informative model

Change elements of a model specification

tidy._LiblineaR

tidy methods for LiblineaR models

Decision trees via rpart

Determine required packages for a model

nearest_neighbor

General Interface for K-Nearest Neighbor Models

tidy methods for glmnet models

General Interface for Multinomial Regression Models

Display currently available engines for a model

Print the model call

Declare a computational engine and specific arguments

Turn a parsnip model object into a tidy tibble

Repair a model call object

Tidy method for null models

General interface for polynomial support vector machines

Tools to Register Models

Objects exported from other packages

General Interface for Parametric Survival Models

General interface for radial basis function support vector machines

Boosted trees via xgboost

varying_args.model_spec

Determine varying arguments

A placeholder function for argument values

General interface for linear support vector machines

type_sum.model_spec

Succinct summary of parsnip object

Resolve a Model Specification for a Computational Engine

Wrapper for stan confidence intervals

General Interface for Parametric Survival Models