2008 MultiClassCostSensitiveBoosting
- (Lozano et al., 2008) ⇒ Aurélie C. Lozano, and Naoki Abe. (2008). “Multi-class Cost-sensitive Boosting with P-norm Loss Functions.” In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2008). doi:10.1145/1401890.1401953
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- http://scholar.google.com/scholar?q=%22Multi-class+cost-sensitive+boosting+with+p-norm+loss+functions%22+2008
- http://portal.acm.org/citation.cfm?doid=1401890.1401953&preflayout=flat#citedby
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Abstract
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establish theoretical guarantees including proof of convergence and convergence rates for the proposed methods. Our theoretical treatment provides interpretations for some of the existing algorithms in terms of the proposed family, including a generalization of the costing algorithm, DSE and GBSE-t, and the Average Cost method. We also experimentally evaluate the performance of our new algorithms against existing methods of cost sensitive boosting, including AdaCost, CSB2, and AdaBoost. M2 with cost-sensitive weight initialization. We show that our proposed scheme generally achieves superior results in terms of cost minimization and, with the use of higher order p-norm loss in certain cases, consistently outperforms the comparison methods, thus establishing its empirical advantage.
References
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Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
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2008 MultiClassCostSensitiveBoosting | Naoki Abe Aurélie C. Lozano | Multi-class Cost-sensitive Boosting with P-norm Loss Functions | KDD-2008 Proceedings | 10.1145/1401890.1401953 | 2008 |