An empirical bias--variance analysis of DECORATE ensemble method at different training sample sizes
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DOI: 10.1080/02664763.2011.620949
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References listed on IDEAS
- Zhang, Chun-Xia & Zhang, Jiang-She, 2008. "A local boosting algorithm for solving classification problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1928-1941, January.
- Rokach, Lior, 2009. "Taxonomy for characterizing ensemble methods in classification tasks: A review and annotated bibliography," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4046-4072, October.
- Tsao, C. Andy & Chang, Yuan-chin Ivan, 2007. "A stochastic approximation view of boosting," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 325-334, September.
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- Chun-Xia Zhang & Guan-Wei Wang & Jun-Min Liu, 2015. "RandGA: injecting randomness into parallel genetic algorithm for variable selection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 630-647, March.
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