A new fuzzy beta naive Bayes classifier

被引：0
|
作者：
de Moraes, Ronei Marcos [1 ]
Gomes Rodrigues, Anny Kerollayny [2 ]
de Melo Gomes Soares, Elaine Anita [2 ]
Machado, Liliane dos Santos [3 ]
机构：
[1] Univ Fed Paraiba, Dept Stat, Joao Pessoa, Paraiba, Brazil
[2] Univ Fed Paraiba, Lab Technol Virtual Teaching & Stat, Joao Pessoa, Paraiba, Brazil
[3] Univ Fed Paraiba, Dept Informat, Joao Pessoa, Paraiba, Brazil
来源：
DEVELOPMENTS OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN COMPUTATION AND ROBOTICS | 2020年 / 12卷
关键词：
Beta statistical distribution; Fuzzy Classification; Fuzzy Statistics; Naive Bayes; AGREEMENT;
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：
There are classifiers based on Beta statistical distribution, but most of them assume data collected without errors and, in some cases, precision of information cannot be guaranteed. This paper presents a proposal of a new classifier named Fuzzy Beta Naive Bayes network (FBetaNB). The mathematical formalism is presented, as well as results of its application on simulated data. A brief comparison among FBetaNB, a classical Beta Naive Bayes classifier and a Naive Bayes classifier was performed. The results obtained showed that the FBetaNB is able to produce the best performance, according to the Overall Accuracy Index, Kappa and Tau Coefficients.
引用
收藏
页码：437 / 445
页数：9
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