Choosing Between Two Classification Learning Algorithms Based on Calibrated Balanced $$5\times 2$$ 5 × 2 Cross-Validated F-Test

Author:

Wang Yu,Li Jihong,Li Yanfang

Funder

National Natural Science Fund of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Reference19 articles.

1. Alpaydin E (1999) Combined $$5\times 2$$ 5 × 2 cv $$F$$ F test for comparing supervised classification learning algorithms. Neural Comput 11(8):1885–1892

2. Wang Y, Ruibo W, Huichen J, Jihong L (2014) Blocked $$3\times 2$$ 3 × 2 cross-validated t-test for comparing supervised classification learning algorithms. Neural Comput 26(1):208–235

3. Bengio Y, Grandvalet Y (2004) No unbiased estimator of the variance of $$K$$ K -fold cross-validation. J Mach Learn Res 5:1089–1105

4. Grandvalet Y, Bengio Y (2006) Hypothesis testing for cross-validation. Technical report. University of Montreal, Montreal

5. Markatou M, Tian H, Biswas S, Hripcsak G (2005) Analysis of variance of cross-validation estimators of the generalization error. J Mach Learn Res 6:1127–1168

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