کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1147144 | 957553 | 2007 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
On nonparametric classification with missing covariates
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آنالیز عددی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
General procedures are proposed for nonparametric classification in the presence of missing covariates. Both kernel-based imputation as well as Horvitz–Thompson-type inverse weighting approaches are employed to handle the presence of missing covariates. In the case of imputation, it is a certain regression function which is being imputed (and not the missing values). Using the theory of empirical processes, the performance of the resulting classifiers is assessed by obtaining exponential bounds on the deviations of their conditional errors from that of the Bayes classifier. These bounds, in conjunction with the Borel–Cantelli lemma, immediately provide various strong consistency results.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 98, Issue 5, May 2007, Pages 1051-1071
Journal: Journal of Multivariate Analysis - Volume 98, Issue 5, May 2007, Pages 1051-1071