relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4751/
title: A multi-label classification framework using the covering based decision table
creator: Pham, Thanh-Huyen
creator: Van-Tuan, Phan
creator: Thi-Ngan, Pham
creator: Thi-Hong, Vuong
creator: Tri-Thanh, Nguyen
creator: Quang-Thuy, Ha
subject: Information Technology (IT)
subject: ISI/Scopus indexed conference
description: 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.
type: Conference or Workshop Item
type: NonPeerReviewed
identifier:   Pham, Thanh-Huyen and Van-Tuan, Phan and Thi-Ngan, Pham and Thi-Hong, Vuong and Tri-Thanh, Nguyen and Quang-Thuy, Ha   A multi-label classification framework using the covering based decision table.  In: 14th Asian Conference on Intelligent Information and Database Systems, Ho Chi Minh City, Vietnam.    (In Press)