Diversity Measures for Building Multiple Classifier Systems Using Genetic Algorithms

被引：0

作者：

Cabrera-Hernandez, Leidys ^{[1
]}

Morales-Hernandez, Alejandro ^{[1
]}

Maria Casas-Cardoso, Gladys ^{[1
]}

机构：

[1] Univ Cent Marta Abreu Las Villas UCLV, Dept Computac, CEI, Fac Matemat Fis & Computac MFC, Santa Clara, Cuba

来源：

COMPUTACION Y SISTEMAS | 2016年 / 20卷 / 04期

关键词：

Diversity measures; multi-classifier; classifiers; genetic algorithms;

D O I：

10.13053/CyS-20-4-2513

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we present the different diversity measures that exist in the literature to decide if a set of classifiers is diverse, aspect that is very important in the creation of multi-classifier systems. The modeling for building multi-classifier systems using meta-heuristic of Genetic Algorithm to ensure the best possible accuracy and greater diversity among the classifiers is presented. Various forms of combination for diversity measures are also enunciated. Finally, we discuss two experiments in which the individual behaviors of diversity measures and their combinations are analyzed.

引用

页码：729 / 747

页数：19

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