Validation of nearest neighbor classifiers

被引:9
作者
Bax, E [1 ]
机构
[1] Univ Richmond, Dept Math & Comp Sci, Richmond, VA 23173 USA
关键词
error bounds; machine learning; nearest neighbor classifier; statistics; validation;
D O I
10.1109/18.887892
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This correspondence presents a method to bound the out-of-sample error rate of a nearest neighbor classifier.(1) The bound is based only on the examples that comprise the classifier. Thus all available examples can be used in the classifier; no examples need to be withheld to compute error bounds. The estimate used in the bound is an extension of the holdout estimate. The difference in error rates between the holdout classifier and the classifier consisting of all available examples is estimated using truncated inclusion and exclusion.
引用
收藏
页码:2746 / 2752
页数:7
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