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partykit (version 1.2-23)

A Toolkit for Recursive Partytioning

Description

A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided based on the new infrastructure. A description of this package was published by Hothorn and Zeileis (2015) .

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Version

Install

install.packages('partykit')

Monthly Downloads

32,024

Version

1.2-23

License

GPL-2 | GPL-3

Maintainer

Last Published

December 2nd, 2024

Functions in partykit (1.2-23)

party-predict

Tree Predictions
partysplit

Binary and Multiway Splits
nodeids

Extract Node Identifiers
varimp

Variable Importance
prune.modelparty

Post-Prune modelparty Objects
partynode

Inner and Terminal Nodes
partynode-methods

Methods for Node Objects
ctree_control

Control for Conditional Inference Trees
ctree

Conditional Inference Trees
mob

Model-based Recursive Partitioning
glmtree

Generalized Linear Model Trees
WeatherPlay

Weather Conditions and Playing a Game
lmtree

Linear Model Trees
extree_fit

Fit Extensible Trees.
party-plot

Visualization of Trees
mob_control

Control Parameters for Model-Based Partitioning
party-methods

Methods for Party Objects
extree_data

Data Preprocessing for Extensible Trees.
panelfunctions

Panel-Generators for Visualization of Party Trees
HuntingSpiders

Abundance of Hunting Spiders
party

Recursive Partytioning
cforest

Conditional Random Forests
nodeapply

Apply Functions Over Nodes
party-coercion

Coercion Functions
model_frame_rpart

Model Frame Method for rpart