> * nominal and numeric input features and predictees (classification and
> regression trees)
> * binary as well as multi-way splits
> * efficient handling of large datasets (200,000 cases/records/instances
> with up to 100 attributes/features/variables)
> * nice to have: integrated feature selection algorithm
I normally use Christian Borgelt's dti package which is quite fast and also
free (GPLed). It supposedly supports building regression trees although I
haven't tried out that feature.
You can find it at
http://fuzzy.cs.uni-magdeburg.de/~borgelt/dtree.html
Cheers,
Yannick Versley
-- Yannick Versley Seminar für Sprachwissenschaft, Abt. Computerlinguistik Wilhelmstr. 19, 72074 Tübingen Tel.: (07071) 29 77352
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