PLS Dimension Reduction for Classification with Microarray Data
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DOI: 10.2202/1544-6115.1075
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Cited by:
- Florian Rohart & Benoît Gautier & Amrit Singh & Kim-Anh Lê Cao, 2017. "mixOmics: An R package for ‘omics feature selection and multiple data integration," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-19, November.
- Schmid Matthias & Hothorn Torsten & Krause Friedemann & Rabe Christina, 2012. "A PAUC-based Estimation Technique for Disease Classification and Biomarker Selection," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(5), pages 1-26, October.
- Boulesteix Anne-Laure, 2006. "Reader's Reaction to "Dimension Reduction for Classification with Gene Expression Microarray Data" by Dai et al (2006)," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 5(1), pages 1-7, June.
- Nguyen Tuan S & Rojo Javier, 2009. "Dimension Reduction of Microarray Data in the Presence of a Censored Survival Response: A Simulation Study," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-40, January.
- González, Javier & Muñoz, Alberto, 2010. "Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification," DES - Working Papers. Statistics and Econometrics. WS ws102713, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Lê Cao Kim-Anh & Rossouw Debra & Robert-Granié Christèle & Besse Philippe, 2008. "A Sparse PLS for Variable Selection when Integrating Omics Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-32, November.
- Chung Dongjun & Keles Sunduz, 2010. "Sparse Partial Least Squares Classification for High Dimensional Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-32, March.
- Asuman Turkmen & Nedret Billor, 2013. "Partial least squares classification for high dimensional data using the PCOUT algorithm," Computational Statistics, Springer, vol. 28(2), pages 771-788, April.
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Keywords
partial least squares; feature extraction; variable selection; boosting; gene expression; discriminant analysis; supervised learning;All these keywords.
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