Unbiased bootstrap error estimation for linear discriminant analysis
نویسندگان
چکیده
منابع مشابه
Unbiased bootstrap error estimation for linear discriminant analysis
Convex bootstrap error estimation is a popular tool for classifier error estimation in gene expression studies. A basic question is how to determine the weight for the convex combination between the basic bootstrap estimator and the resubstitution estimator such that the resulting estimator is unbiased at finite sample sizes. The well-known 0.632 bootstrap error estimator uses asymptotic argume...
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ژورنال
عنوان ژورنال: EURASIP Journal on Bioinformatics and Systems Biology
سال: 2014
ISSN: 1687-4153
DOI: 10.1186/s13637-014-0015-0