Multi-label classification using ensembles of pruned sets

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2008, Pages 995-1000

  Read, Jesse ^a   Pfahringer, Bernhard ^a   Holmes, Geoff ^a  

^a UNIVERSITY OF WAIKATO   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION PROCESS; COMPLEX DATA; DATA SETS; EXPERIMENTAL EVALUATION; LABEL SETS; MULTI-LABEL;

INFORMATION MANAGEMENT; MINING;

LABELS;

EID: 67049088703     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2008.74     Document Type: Conference Paper

References (12)

1. CALO project: Enron email dataset. URL: http://www-2.cs.cmu.edu/~enron/.
2. Computational medical center: Medical NLP challenge. URL: http://www.computationalmedicine.org/challenge/index.php.
3. UC Berkeley enron email analysis project: UC Berkeley enron email analysis. URL: http://bailando.sims.berkeley.edu/enron-email.html.
4. S. Godbole and S. Sarawagi. Discriminative methods for multi-labeled classification. In 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2004.
5. D. Lewis, Y. Yang, T. Rose, and F. Li. RCV1: A New Benchmark Collection for Text Categorization Research. The Journal of Machine Learning Research, 5:361-397, 2004.
6. A. K. McCallum. Multi-label text classification with a mixture model trained by EM. In Association for the Advancement of Artificial Intelligence workshop on text learning, 1999.
7. R. E. Schapire and Y. Singer. Boostexter: A boostingbased system for text categorization. Machine Learning, 39(2/3):135-168, 2000. (Pubitemid 30594821)
8. G. Tsoumakas and I. Katakis. Multi label classification: An overview. International Journal of Data Warehousing and Mining, 3(3), 2007.
9. G. Tsoumakas and I. Vlahavas. Random k-labelsets: An ensemble method for multilabel classification. In Proceedings of the 18th European Conference on Machine Learning (ECML 2007, 2007.
10. C. Vens, J. Struyf, L. Schietgat, S. D?zeroski, and H. Blockeel. Decision trees for hierarchical multi-label classification. Machine Learning, 73(2):185-214, 2008.
11. I. H. Witten and E. Frank. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, San Francisco, second edition, 2005.
12. M.-L. Zhang and Z.-H. Zhou. A k-nearest neighbor based algorithm for multi-label classification. volume 2, pages 718- 721. The IEEE Computational Intelligence Society, 2005.