PT Journal
AU Francesco Ciompi
   Oriol Pujol
   Petia Radeva
TI ECOC-DRF: Discriminative random fields based on error correcting output codes
SO Pattern Recognition
JI PR
PY 2014
BP 2193
EP 2204
VL 47
IS 6
DI 10.1016/j.patcog.2013.12.007
DE Discriminative random fields; Error-correcting output codes; Multi-class classification; Graphical models
AB We present ECOC-DRF, a framework where potential functions for Discriminative Random Fields are formulated as an ensemble of classifiers. We introduce the label trick, a technique to express transitions in the pairwise potential as meta-classes. This allows to independently learn any possible transition between labels without assuming any pre-defined model. The Error Correcting Output Codes matrix is used as ensemble framework for the combination of margin classifiers. We apply ECOC-DRF to a large set of classification problems, covering synthetic, natural and medical images for binary and multi-class cases, outperforming state-of-the art in almost all the experiments.
ER