Exact bagging with k-nearest neighbour classifiers

被引：0

作者：

Caprile, B ^{[1
]}

Merler, S ^{[1
]}

Furlanello, C ^{[1
]}

Jurman, G ^{[1
]}

机构：

[1] ITC irst, Ctr Ric Sci & Technol, I-38050 Trento, Italy

来源：

MULTIPLE CLASSIFIER SYSTEMS, PROCEEDINGS | 2004年 / 3077卷

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A formula is derived for the exact computation of Bagging classifiers when the base model adopted is k-Nearest Neighbour (k-NN). The formula, that holds in any dimension and does not require the extraction of bootstrap replicates, proves that Bagging cannot improve 1-Nearest Neighbour. It also proves that, for k > 1, Bagging has a smoothing effect on k-NN. Convergence of empirically bagged k-NN predictors to the exact formula is also considered. Efficient approximations to the exact formula are derived, and their applicability to practical cases is illustrated.

引用

页码：72 / 81

页数：10

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