Feating

Description:-

Feating (Feature-Subspace Aggregating) is an ensemble learning approach that constructs a classification ensemble comprising a set of local models. It is distinguished from most previous ensemble learning algorithms by being effective at reducing the error of both stable and unstable learners. In particular, it is effective at reducing the error of SVM. License under GNU General Public License (GPL)

Reference:-

Ting, K.M., J. Wells, S. Tan, S. Teng, and G.I. Webb (2011). Feature-subspace aggregating: Ensembles for stable and unstable learners. Machine Learning 82(3): 375-397.

Last edited on 2011-09-28

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