Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data
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- Peter Hall & J. S. Marron & Amnon Neeman, 2005. "Geometric representation of high dimension, low sample size data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(3), pages 427-444, June.
- Wickham, Hadley & Cook, Dianne & Hofmann, Heike & Buja, Andreas, 2011. "tourr: An R Package for Exploring Multivariate Data with Projections," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i02).
- Jeongyoun Ahn & J. S. Marron, 2010. "The maximal data piling direction for discrimination," Biometrika, Biometrika Trust, vol. 97(1), pages 254-259.
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Keywords
data visualisation; grand tour; statistical computing; statistical graphics; multivariate data; dynamic graphics; data science; machine learning;All these keywords.
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