کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
532618 869974 2009 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
On the sampling distribution of resubstitution and leave-one-out error estimators for linear classifiers
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
On the sampling distribution of resubstitution and leave-one-out error estimators for linear classifiers
چکیده انگلیسی

Error estimation is a problem of high current interest in many areas of application. This paper concerns the classical problem of determining the performance of error estimators in small-sample settings under a Gaussianity parametric assumption. We provide here for the first time the exact sampling distribution of the resubstitution and leave-one-out error estimators for linear discriminant analysis (LDA) in the univariate case, which is valid for any sample size and combination of parameters (including unequal variances and sample sizes for each class). In the multivariate case, we provide a quasi-binomial approximation to the distribution of both the resubstitution and leave-one-out error estimators for LDA, under a common but otherwise arbitrary class covariance matrix, which is assumed to be known in the design of the LDA discriminant. We provide numerical examples, using both synthetic and real data, that indicate that these approximations are accurate, provided that LDA classification error is not too large.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 42, Issue 11, November 2009, Pages 2705–2723
نویسندگان
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