well, how difficult to code random forest with sas macro + proc split? if you are lack of sas programming skill, then you are correct that you have to wait for 8 years :-) i don't know how much sas experience you have. as far as i know, both bagging and boosting have been implemented in sas em for a while, together with other cut-edge modeling tools such as svm / nnet.
On Fri, Jun 19, 2009 at 4:18 PM, Tobias Verbeke<tobias.verb...@openanalytics.be> wrote: > Wensui Liu wrote: > >> in terms of the richness of features and ability to handle large >> data(which is normal in bank), SAS EM should be on top of others. > > Should be ? That is not at all my experience. > SAS EM is very much lagging behind current > research. You will find variants of random forests > in R that will not be in SAS for the next 8 years, > to give just one example. > >> however, it is not cheap. >> in terms of algorithm, split procedure in sas em can do >> chaid/cart/c4.5, if i remember correctly. > > These are techniques of the 80s and 90s > (which proves my point). CART is in rpart and > an implementation of C4.5 can be accessed > through RWeka. For the oldest one (CHAID, 1980), > there might be an implementation soon: > > http://r-forge.r-project.org/projects/chaid/ > > but again there have been quite some improvements > in the last decade as well: > > http://cran.r-project.org/web/views/MachineLearning.html > > HTH, > Tobias > >> On Fri, Jun 19, 2009 at 2:35 PM, Carlos J. Gil >> Bellosta<c...@datanalytics.com> wrote: >>> >>> Dear R-helpers, >>> >>> I had a conversation with a guy working in a "business intelligence" >>> department at a major Spanish bank. They rely on recursive partitioning >>> methods to rank customers according to certain criteria. >>> >>> They use both SAS EM and Salford Systems' CART. I have used package R >>> part in the past, but I could not provide any kind of feature comparison >>> or the like as I have no access to any installation of the first two >>> proprietary products. >>> >>> Has anybody experience with them? Is there any public benchmark >>> available? Is there any very good --although solely technical-- reason >>> to pay hefty software licences? How would the algorithms implemented in >>> rpart compare to those in SAS and/or CART? >>> >>> Best regards, >>> >>> Carlos J. Gil Bellosta >>> http://www.datanalytics.com >>> >>> ______________________________________________ >>> R-help@r-project.org mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> >> >> > > -- ============================== WenSui Liu Blog : statcompute.spaces.live.com Tough Times Never Last. But Tough People Do. - Robert Schuller ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
