evtree v1.0-2

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Evolutionary Learning of Globally Optimal Trees

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.

Functions in evtree

Name Description
StatlogHeart Statlog Heart
evtree.control Control for evtree
ContraceptiveChoice Contraceptive Method Choice
BBBClub Bookbinder's Book Club
evtree Evolutionary Learning of Globally Optimal Trees
GermanCredit Statlog German Credit
MAGICGammaTelescope MAGIC Gamma Telescope
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Date 2017-01-23
LazyData yes
License GPL-2 | GPL-3
Repository CRAN
Repository/R-Forge/Project partykit
Repository/R-Forge/Revision 1075
Repository/R-Forge/DateTimeStamp 2017-01-23 14:50:23
Date/Publication 2017-01-24 19:43:00
NeedsCompilation yes
Packaged 2017-01-23 15:06:21 UTC; rforge

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