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partykit (version 1.1-1)

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.

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Version

Install

install.packages('partykit')

Monthly Downloads

28,757

Version

1.1-1

License

GPL-2 | GPL-3

Maintainer

Torsten Hothorn

Last Published

September 20th, 2016

Functions in partykit (1.1-1)

lmtree

Linear Model Trees
ctree

Conditional Inference Trees
HuntingSpiders

Abundance of Hunting Spiders
mob

Model-based Recursive Partitioning
model.frame.rpart

Model Frame Method for rpart
nodeapply

Apply Functions Over Nodes
glmtree

Generalized Linear Model Trees
ctree_control

Control for Conditional Inference Trees
mob_control

Control Parameters for Model-Based Partitioning
cforest

Conditional Random Forests
party-methods

Methods for Party Objects
party-coercion

Coercion Functions
party-predict

Tree Predictions
party-plot

Visualization of Trees
panelfunctions

Panel-Generators for Visualization of Party Trees
nodeids

Extract Node Identifiers
partynode

Inner and Terminal Nodes
partynode-methods

Methods for Node Objects
palmtree

Partially Additive (Generalized) Linear Model Trees
party

Recursive Partytioning
WeatherPlay

Weather Conditions and Playing a Game
partysplit

Binary and Multiway Splits