R has been around for a long time and has long been a standard.
Pythons sklearn is indeed an 'emerging star'.
Personally I use both.
Also have a look at some of the many stand alone tools vowpal wabbit (blazingly fast for regression learning, scales to ridiculous amounts of data) is superb, as is sofia-ml (for clustering, again scales quite well)
I tie them all together in python, since there are python bindings for R, and you can use pythons 'Subprocess' module to pipe commands and data for commandline tools that don't have python bindings.
There are other useful tools as well - I use Weka for some of my initial visualization and when I'm feeling lazy and want a quick result.