[R] Comparison of SAS & R/Splus
Ko-Kang Kevin Wang
kwan022 at stat.auckland.ac.nz
Thu Sep 4 22:19:46 CEST 2003
On Thu, 4 Sep 2003, Paul, David A wrote:
> I am one of only 5 or 6 people in my organization making the
> effort to include R/Splus as an analysis tool in everyday work -
> the rest of my colleagues use SAS exclusively.
>
> Today, one of them made the assertion that he believes the
> numerical algorithms in SAS are superior to those in Splus
> and R -- ie, optimization routines are faster in SAS, the SAS
I can't say for the optimisation routines, but I have found this...
When I was doing my MSc thesis, using tree-based models and neural
networks for classifications, I discovered something interesting.
Using SAS Enterprise Miner (SAS EM), its Tree Node is far more efficient
than the rpart package. Using the same (or very similar at least) parameter
settings, SAS EM can produce a tree in about 1 minute while it would take
rpart 5 ~ 6 minutes (same data, same machine....). Having said that, I
still prefer rpart as it can draw a beautiful tree, whereas it is very
difficult to fit the graphical tree produced by SAS EM into one A4 page --
in the end I had to use the text tree.
However, the Neural Network node in SAS EM is less efficient than nnet.
The time it takes to fit a neural network in R using nnet is much
faster....
--
Cheers,
Kevin
------------------------------------------------------------------------------
"On two occasions, I have been asked [by members of Parliament],
'Pray, Mr. Babbage, if you put into the machine wrong figures, will
the right answers come out?' I am not able to rightly apprehend the
kind of confusion of ideas that could provoke such a question."
-- Charles Babbage (1791-1871)
---- From Computer Stupidities: http://rinkworks.com/stupid/
--
Ko-Kang Kevin Wang
Master of Science (MSc) Student
SLC Tutor and Lab Demonstrator
Department of Statistics
University of Auckland
New Zealand
Homepage: http://www.stat.auckland.ac.nz/~kwan022
Ph: 373-7599
x88475 (City)
x88480 (Tamaki)
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