Ensembles of similarity-based models

被引：0

作者：

Duch, W ^{[1
]}

Grudzinski, K ^{[1
]}

机构：

[1] Nicholas Copernicus Univ, Dept Comp Methods, PL-87100 Torun, Poland

来源：

INTELLIGENT INFORMATION SYSTEMS 2001 | 2001年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Ensembles of independent classifiers are usually more accurate and show smaller variance than individual classifiers. Methods of selection of Similarity Based Models (SBM) that should be included in an ensemble are discussed. Standard k-NN, weighted k-NN, ensembles of weighted models and ensembles of averaged weighted models are considered. Ensembles of competent models are introduced. Results of numerical experiments on benchmark and real-world datasets are presented.

引用

页码：75 / 85

页数：11

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