请教一个有关决策树剪枝的问题！！！

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请教各位高人一个问题。我想做一些有关决策树剪枝方面的研究，目前用到的Ｒ包主要是ｐａｒｔｙ和ｒｐａｒｔ，里边主要支持的决策树剪枝方法是Ｂｒｅｉｍａｎ的ＣＣＰ代价复杂度剪枝方法。通过阅读有关文献，其它常用的方法还有ＰＥＰ和ＲＥＰ等方法，请问R软件哪个包或者哪个语句支持这些剪枝算法？或者能否提供一下雨决策树剪枝有关的语句和软件包？另外，除了CART树，C4.5算法和ID3算法，R软件是否支持？谢谢。

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关键词：决策树 CART r软件 软件包 CAR 软件包

C4.5 不知道，但是C5有相应的R软件包，名字叫C50。

同时在R的Task View上，有下面的描述：

Recursive Partitioning : Tree-structured models for regression, classification and survival analysis, following the ideas in the CART book, are implemented in rpart (shipped with base R) and tree. Package rpart is recommended for computing CART-like trees. A rich toolbox of partitioning algorithms is available in Weka , package RWeka provides an interface to this implementation, including the J4.8-variant of C4.5 and M5. The Cubist package fits rule-based models (similar to trees) with linear regression models in the terminal leaves, instance-based corrections and boosting. The C50 package can fit C5.0 classification trees, rule-based models, and boosted versions of these.
Two recursive partitioning algorithms with unbiased variable selection and statistical stopping criterion are implemented in package party. Function ctree() is based on non-parametrical conditional inference procedures for testing independence between response and each input variable whereas mob() can be used to partition parametric models. Extensible tools for visualizing binary trees and node distributions of the response are available in package party as well.
An adaptation of rpart for multivariate responses is available in package mvpart. For problems with binary input variables the package LogicReg implements logic regression. Graphical tools for the visualization of trees are available in package maptree.
Trees for modelling longitudinal data by means of random effects is offered by package REEMtree. Partitioning of mixture models is performed by RPMM.
Computational infrastructure for representing trees and unified methods for predition and visualization is implemented in partykit. This infrastructure is used by package evtree to implement evolutionary learning of globally optimal trees. Oblique trees are available in package oblique.tree.

http://cran.r-project.org/web/views/MachineLearning.html

Aharach 发表于 2014-4-26 03:34
C4.5 不知道，但是C5有相应的R软件包，名字叫C50。

同时在R的Task View上，有下面的描述：

非常感谢！