A Novel Multiclass Text Classification Algorithm Based on Multiconlitron
Authors
Yuping Qin, Fengfeng Qiu, Qiangkui Leng, Aihua Zhang
Corresponding Author
Yuping Qin
Available Online April 2016.
- DOI
- 10.2991/emim-16.2016.173How to use a DOI?
- Keywords
- Multiconlitron; Multiclass classification; One-against-one; Support vector machines
- Abstract
A novel multiclass text classification algorithm based on multiconlitron is proposed. The multiconlitron is constructed for each possible pair of classes in sample space, each of which is used to separate two classes. For the sample to be classified, every multiconlitron is used to judge its class,and vote for the corresponding class. The final class of the sample is determined by the number of votes. The classification experiments are done on Reuters 21578, and the experimental results show that the proposed algorithm has better performance. Compared with multiclass support vector machines 1-a-1, 1-a-r and DAGSVM, while ensuring the classification accuracy, it improves the classification speed and training speed greatly.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yuping Qin AU - Fengfeng Qiu AU - Qiangkui Leng AU - Aihua Zhang PY - 2016/04 DA - 2016/04 TI - A Novel Multiclass Text Classification Algorithm Based on Multiconlitron BT - Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society PB - Atlantis Press SP - 843 EP - 848 SN - 2352-538X UR - https://doi.org/10.2991/emim-16.2016.173 DO - 10.2991/emim-16.2016.173 ID - Qin2016/04 ER -