Hi all,
I've been asked and I'm trying to figure out what are the major differences 
between Mahout and WEKA concerning classification, clustering and assoc 
rules(PFPGrowth). My understanding so far is that:- Mahout supports 
unsupervised algorithms; WEKA also supports supervised through its UI.- Mahout 
scales much better while WEKA is memory bound.- Mahout is targeting developers 
directly; WEKA mainly data mining analysts.- WEKA supports automating detection 
of classification algorithms. does Mahout have something similar?- Anything 
important that I've missed?
If anyone can provide any insight that would be great. Thanks.
/qf

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