Hypothesis diversity in ensemble classification

被引：0

作者：

Saitta, Lorenza ^{[1
]}

机构：

[1] Univ Piemonte Orientale, Dipartimento Informat, Alessandria, Italy

来源：

FOUNDATIONS OF INTELLIGENT SYSTEMS, PROCEEDINGS | 2006年 / 4203卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper discusses the issue of hypothesis diversity in ensemble classifiers. The measures of diversity previously proposed in the literature are analyzed inside a unifying framework based on Monte Carlo stochastic algorithms. The paper shows that no measure is useful to predict ensemble performance, because all of them have only a very loose relation with the expected accuracy of the classifier.

引用

页码：662 / 670

页数：9

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