CRAN/E | evtree

evtree

Evolutionary Learning of Globally Optimal Trees

Installation

About

Commonly used classification and regression tree methods like the CART algorithm are recursive partitioning methods that build the model in a forward stepwise search. Although this approach is known to be an efficient heuristic, the results of recursive tree methods are only locally optimal, as splits are chosen to maximize homogeneity at the next step only. An alternative way to search over the parameter space of trees is to use global optimization methods like evolutionary algorithms. The 'evtree' package implements an evolutionary algorithm for learning globally optimal classification and regression trees in R. CPU and memory-intensive tasks are fully computed in C++ while the 'partykit' package is leveraged to represent the resulting trees in R, providing unified infrastructure for summaries, visualizations, and predictions.

Citation evtree citation info

Key Metrics

Version 1.0-8
R ≥ 3.3.0
Published 2019-05-26 1768 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks evtree results

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Maintainer

Maintainer

Thomas Grubinger

ThomasGrubinger@gmail.com

Authors

Thomas Grubinger

aut / cre

Achim Zeileis

aut

Karl-Peter Pfeiffer

aut

Material

NEWS
Reference manual
Package source

In Views

MachineLearning

Vignettes

Evolutionary Learning of Globally Optimal Classification and Regression Trees in R

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

evtree archive

Depends

R ≥ 3.3.0
partykit

Suggests

Formula
kernlab
lattice
mlbench
multcomp
party
rpart
xtable

Reverse Imports

insurancerating

Reverse Suggests

fscaret
mlr
r2pmml
stablelearner