Quick guide into training highly imbalanced data sets
Max Kuhn covers this well in Ch16 of Applied Predictive Modeling.     
As mentioned in the linked thread, imbalanced data is essentially a cost sensitive training problem. Thus any cost sensitive approach is applicable to imbalanced data.
There are a large number of such approaches. Not all implemented in R: C50, weighted SVMs are options. Jous-boost. Rusboost I think is only available as Matlab code. 
I don't use Weka, but believe it has a large number of cost sensitive classifiers. 
Handling imbalanced datasets: A review: Sotiris Kotsiantis, Dimitris Kanellopoulos, Panayiotis Pintelas'
On the Class Imbalance Problem: Xinjian Guo, Yilong Yin, Cailing Dong, Gongping Yang, Guangtong Zhou