An improved multi-label classification based on label ranking and delicate boundary SVM

Benhui Chen, Weifeng Gu, Takayuki Furuzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, an improved multi-label classification is proposed based on label ranking and delicate decision boundary SVM. Firstly, an improved probabilistic SVM with delicate decision boundary is used as the scoring method to obtain a proper label rank. It can improve the probabilistic label rank by introducing the information of overlapped training samples into learning procedure. Secondly, a threshold selection related with input instance and label rank is proposed to decide the classification results. It can estimate an appropriate threshold for each testing instance according to the characteristics of instance and label rank. Experimental results on four multi-label benchmark datasets show that the proposed method improves the performance of classification efficiently, compared with binary SVM method and some existing well-known methods.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
DOIs
Publication statusPublished - 2010
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona
Duration: 2010 Jul 182010 Jul 23

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
CityBarcelona
Period10/7/1810/7/23

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ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Chen, B., Gu, W., & Furuzuki, T. (2010). An improved multi-label classification based on label ranking and delicate boundary SVM. In Proceedings of the International Joint Conference on Neural Networks [5596350] https://doi.org/10.1109/IJCNN.2010.5596350

An improved multi-label classification based on label ranking and delicate boundary SVM. / Chen, Benhui; Gu, Weifeng; Furuzuki, Takayuki.

Proceedings of the International Joint Conference on Neural Networks. 2010. 5596350.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, B, Gu, W & Furuzuki, T 2010, An improved multi-label classification based on label ranking and delicate boundary SVM. in Proceedings of the International Joint Conference on Neural Networks., 5596350, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, 10/7/18. https://doi.org/10.1109/IJCNN.2010.5596350
Chen B, Gu W, Furuzuki T. An improved multi-label classification based on label ranking and delicate boundary SVM. In Proceedings of the International Joint Conference on Neural Networks. 2010. 5596350 https://doi.org/10.1109/IJCNN.2010.5596350
Chen, Benhui ; Gu, Weifeng ; Furuzuki, Takayuki. / An improved multi-label classification based on label ranking and delicate boundary SVM. Proceedings of the International Joint Conference on Neural Networks. 2010.
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