Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
There are two ways to build a regression tree in Weka:
- weka.classifiers.trees.m5.M5P -R
Both are different from CART though, mainly in the way they prune the tree. M5P uses the standard M5 pruning criterion, and REPTree uses reduced-error pruning. Both pruning techniques are not as good as CART's one (i.e. they will produce a larger tree than really needed) but they are faster.
Source: Weka FAQ