Description:

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.

Changes to previous version:

Fetched by r-cran-robot on 2014-05-01 00:00:05.459097

BibTeX Entry: Download

Supported Operating Systems: Agnostic

Tags: R-Cran

Archive: download here

Other available revisons

Version	Changelog	Date
0.1-4	Fetched by r-cran-robot on 2014-05-01 00:00:05.459097	December 1, 2013, 00:00:04
0.1-3	Fetched by r-cran-robot on 2013-11-01 00:00:04.651985	July 1, 2013, 00:00:05
0.1-2	Fetched by r-cran-robot on 2013-06-01 00:00:06.431029	May 1, 2012, 00:00:05
0.1-1	Fetched by r-cran-robot on 2012-04-01 00:00:05.044729	February 1, 2012, 00:00:05

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