当前位置: X-MOL 学术Pattern Recogn. Lett. › 论文详情
Multilabel naïve Bayes classification considering label dependence
Pattern Recognition Letters ( IF 3.255 ) Pub Date : 2020-06-25 , DOI: 10.1016/j.patrec.2020.06.021
Hae-Cheon Kim; Jin-Hyeong Park; Dae-Won Kim; Jaesung Lee

Multilabel classification is the task of assigning relevant labels to an instance, and it has received considerable attention in recent years. This task can be performed by extending a single-label classifier, such as the naïve Bayes classifier, to utilize the useful relations among labels for achieving better multilabel classification accuracy. However, the conventional multilabel naïve Bayes classifier treats each label independently and hence neglects the relations among labels, resulting in degenerated accuracy. We propose a new multilabel naïve Bayes classifier that considers the relations or dependence among labels. Experimental results show that the proposed method outperforms conventional multilabel classifiers.
更新日期:2020-06-27

 

全部期刊列表>>
材料学研究精选
Springer Nature Live 产业与创新线上学术论坛
胸腔和胸部成像专题
自然科研论文编辑服务
ACS ES&T Engineering
ACS ES&T Water
屿渡论文,编辑服务
杨超勇
周一歌
华东师范大学
南京工业大学
清华大学
中科大
唐勇
跟Nature、Science文章学绘图
隐藏1h前已浏览文章
中洪博元
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
福州大学
南京大学
王杰
左智伟
湖南大学
清华大学
吴杰
赵延川
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug