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Unfortunatelly I have to disagree,
LIBSVM is able to deal with multiclass classification, and if fact there's a connector to LIBSVM in RM, but then the LIBSVM results stays constrained by this strange architecture of Polynomial and Binomail that exists only in Rapidminer.
Even a simple IRIS problem, is not possible to obtain a simple AUC, F-Measure, or ROC, and the Polynomial by Binomial classification or regression, simply doesn't work.
There is mathematical formulation to abandon this polynomial and binomial architecture, and this is a widespread methodology in any machine learning tool like Weka, R, Phyton libs, etc.
I think it's time to abandon this Poly/Bin architecture, but this involves deep changes in the RM structure.
The Polynomial by Binomial classification or regression, is working fine, and I can't disagree and complain about Poly/Bin architecture, without to propose possible solutions and to contribute some how with this great platform. Possible solutions for this problem are discussed in this topic.