Title :
Probabilistic Classification Using Data Mining
Author :
Yuichiro Kase;Takao Miura
Author_Institution :
Dept. of Adv. Sci., HOSEI Univ., Koganei, Japan
Abstract :
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.
Keywords :
"Training data","Marine vehicles","Niobium","Probabilistic logic","Maximum likelihood estimation","Association rules"
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
DOI :
10.1109/WI-IAT.2015.169