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18th International Conference on Pattern Recognition (ICPR'06) Volume 4
Robust Multiclass Ensemble Classifiers via Symmetric Functions
Hong Kong
August 20-August 24
ISBN: 0-7695-2521-0
| ASCII Text | x | ||
| Patrice Lefaucheur, Richard Nock, "Robust Multiclass Ensemble Classifiers via Symmetric Functions," Pattern Recognition, International Conference on, vol. 4, pp. 136-139, 18th International Conference on Pattern Recognition (ICPR'06) Volume 4, 2006. | |||
| BibTex | x | ||
| @article{ 10.1109/ICPR.2006.1010, author = {Patrice Lefaucheur and Richard Nock}, title = {Robust Multiclass Ensemble Classifiers via Symmetric Functions}, journal ={Pattern Recognition, International Conference on}, volume = {4}, year = {2006}, issn = {1051-4651}, pages = {136-139}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.1010}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Pattern Recognition, International Conference on TI - Robust Multiclass Ensemble Classifiers via Symmetric Functions SN - 1051-4651 SP136 EP139 A1 - Patrice Lefaucheur, A1 - Richard Nock, PY - 2006 KW - Ensemble classifiers KW - Symmetric functions. VL - 4 JA - Pattern Recognition, International Conference on ER - | |||
We introduce a generalization to the multiclass framework of a previous approach to Boosting by constructing symmetric functions. This approach contrasts with the usual ADABOOST-type Boosting algorithms using linear separators. Indeed, multiclass induction does not necessitate combination tricks such as those for linear separators, and it achieves some novel agnostic learning properties, as well as significant malicious noise tolerance. Experiments on a large testbed against ADABOOST and C4.5 display the efficiency of the approach proned.
Index Terms:
Ensemble classifiers, Symmetric functions.
Citation:
Patrice Lefaucheur, Richard Nock, "Robust Multiclass Ensemble Classifiers via Symmetric Functions," icpr, vol. 4, pp.136-139, 18th International Conference on Pattern Recognition (ICPR'06) Volume 4, 2006
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