TY  - INPR
ID  - SisLab4751
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4751/
A1  - Pham, Thanh-Huyen
A1  - Van-Tuan, Phan
A1  - Thi-Ngan, Pham
A1  - Thi-Hong, Vuong
A1  - Tri-Thanh, Nguyen
A1  - Quang-Thuy, Ha
N2  - Multi-label classification (MLC) has recently drawn much attention thanks to its usefulness and omnipresence in real-world applications, in which objects may be characterized by more than one labels. One of the challenges in MLC is to deter-mine the relationship between the labels due to the fact that there is not any as-sumptions of the independence between labels, and there is not any information and knowledge about these relationships in a training dataset. Recently, many re-searches have focused on exploiting these label relationships to enhance the per-formance of the classification, however there have not many of them using the covering rough set. This paper propose a multi-label classification algorithm named CDTML, based on ML-KNN algorithm, using covering based decision table which exploits the relationship between labels to enhance the performance of the multi-label classifier. The experimental results on serveral dataset of Enron, Medical and a Vietnamese dataset of hotel reviews shown the effectiveness of the proposed algorithm.
TI  - A multi-label classification framework using the covering based decision table
AV  - none
M2  - Ho Chi Minh City, Vietnam
T2  - 14th Asian Conference on Intelligent Information and Database Systems
ER  -