Multi-Label Classification Using Labelled Association

被引：0

作者：

Kase, Yuichiro ^{[1
]}

Miura, Takao ^{[1
]}

机构：

[1] Hosei Univ, Dept Adv Sci, Kajinocho 3-7-2, Tokyo, Japan

来源：

2015 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS AND SIGNAL PROCESSING (PACRIM) | 2015年

关键词：

Classification; Multi-label Classification; Data Mining;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this investigation we discuss a multi-label classification problem where documents may have several labels. We put our focus on dependencies among labels in a probabilistic manner, and we extract characteristic features in a form of probabilistic distribution functions by data mining techniques. We show some experimental results, i.e., dependencies among items/labels to see the effectiveness of the approach.

引用

页码：90 / 95

页数：6