(Psycho-)analysis of benchmark experiments: A formal framework for investigating the relationship between data sets and learning algorithms
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DOI: 10.1016/j.csda.2013.08.007
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References listed on IDEAS
- Achim Zeileis & Kurt Hornik, 2007. "Generalized M‐fluctuation tests for parameter instability," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(4), pages 488-508, November.
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- Torti, Francesca & Perrotta, Domenico & Atkinson, Anthony C. & Riani, Marco, 2012. "Benchmark testing of algorithms for very robust regression: FS, LMS and LTS," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2501-2512.
- Givens, G.H. & Beveridge, J.R. & Phillips, P.J. & Draper, B. & Lui, Y.M. & Bolme, D., 2013. "Introduction to face recognition and evaluation of algorithm performance," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 236-247.
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- Anne-Laure Boulesteix & Robert Hable & Sabine Lauer & Manuel J. A. Eugster, 2015. "A Statistical Framework for Hypothesis Testing in Real Data Comparison Studies," The American Statistician, Taylor & Francis Journals, vol. 69(3), pages 201-212, August.
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Keywords
Benchmark experiments; Data set characterization; Recursive partitioning; Preference scaling; Bradley–Terry model;All these keywords.
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