Sparse semiparametric discriminant analysis
نویسندگان
چکیده
منابع مشابه
Sparse semiparametric discriminant analysis
In recent years, a considerable amount of work has been devoted to generalizing linear discriminant analysis to overcome its incompetence for high-dimensional classification (Witten and Tibshirani, 2011, Cai and Liu, 2011, Mai et al., 2012 and Fan et al., 2012). In this paper, we develop high-dimensional sparse semiparametric discriminant analysis (SSDA) that generalizes the normal-theory discr...
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In recent years, a considerable amount of work has been devoted to generalizing linear discriminant analysis to overcome its incompetence for high-dimensional classification (Witten & Tibshirani 2011, Cai & Liu 2011, Mai et al. 2012, Fan et al. 2012). In this paper, we develop high-dimensional semiparametric sparse discriminant analysis (HD-SeSDA) that generalizes the normal-theory discriminant...
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Classi cation in high-dimensional feature spaces where interpretation and dimension reduction are of great importance is common in biological and medical applications. For these applications standard methods such as microarrays, 1D NMR, and spectroscopy have become everyday tools for measuring thousands of features in samples of interest. The samples are often costly and therefore many problems...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2015
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2014.12.009