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