Improving multi-label classification using semi-supervised learning and dimensionality reduction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7458 LNAI, Issue , 2012, Pages 423-434

  Pacharawongsakda, Eakasit ^a   Nattee, Cholwich ^a   Theeramunkong, Thanaruk ^a  

^a THAMMASAT UNIVERSITY   (Thailand)

Author keywords

co training; dimensionality reduction; multi label classification; semi supervised learning; Singular Value Decomposition; SVD

Indexed keywords

ADAPTIVE THRESHOLDS; CLASSIFICATION PERFORMANCE; CO-TRAINING; COMPUTATIONAL TIME; DIMENSIONALITY REDUCTION; FEATURE SPACE; HIGH DIMENSIONALITY; LABEL SPACE; LABELED DATA; MULTI-LABEL; MULTIPLE CLASS; ORTHOGONAL PROPERTY; PARALLEL COMPUTATION; REAL-WORLD DATASETS; REGRESSION METHOD; SEMI-SUPERVISED LEARNING; SEMI-SUPERVISED LEARNING METHODS; TRAINING DATA; UNLABELED DATA;

ARTIFICIAL INTELLIGENCE; DATA REDUCTION; SINGULAR VALUE DECOMPOSITION; SUPERVISED LEARNING;

CLASSIFICATION (OF INFORMATION);

EID: 84867671576     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-32695-0_38     Document Type: Conference Paper

References (11)

1. Blum, A., Mitchell, T.: Combining labeled and unlabeled data with co-training. In: Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT 1998, pp. 92-100. ACM, New York (1998)
2. Chen, G., Song, Y., Wang, F.: Semi-supervised multi-label learning by solving a sylvester equation. In: Proceedings of the 8th SIAM Conference on Data Mining (SDM), SDM 2008, pp. 410-419 (2008)
3. Liu, Y., Jin, R., Yang, L.: Semi-supervised multi-label learning by constrained non-negative matrix factorization. In: Proceedings of the 21st AAAI Conference on Artificial Intelligence, AAAI 2006, pp. 421-426. AAAI Press (2006)
4. Pacharawongsakda, E., Theeramunkong, T.: Towards More Efficient Multi-label Classification Using Dependent and Independent Dual Space Reduction. In: Tan, P.-N., Chawla, S., Ho, C.K., Bailey, J. (eds.) PAKDD 2012, Part II. LNCS, vol. 7302, pp. 383-394. Springer, Heidelberg (2012)
5. Qian, B., Davidson, I.: Semi-supervised dimension reduction for multi-label classification. In: Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010, pp. 569-574. AAAI Press (2010)
6. Read, J., Pfahringer, B., Holmes, G., Frank, E.: Classifier Chains for Multi-label Classification. In: Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009, Part II. LNCS, vol. 5782, pp. 254-269. Springer, Heidelberg (2009)
7. Schapire, R., Singer, Y.: Boostexter: A boosting-based system for text categorization. Machine Learning 39(2/3), 135-168 (2000)
8. Tai, F., Lin, H.-T.: Multi-label classification with principle label space transformation. In: Proceedings of the 2nd International Workshop on Learning from Multi-Label Data, MLD 2010, pp. 45-52 (2010)
9. Tsoumakas, G., Katakis, I., Vlahavas, I.: Mining Multi-label Data. In: Data Mining and Knowledge Discovery Handbook, 2nd edn. Springer (2010)
10. Zhang, Y., Zhou, Z.-H.: Multilabel dimensionality reduction via dependence maximization. ACM Transactions on Knowledge Discovery from Data (TKDD) 4(3), 1-21 (2010)
11. Zhou, Z.H., Li, M.: Semi-supervised regression with co-training style algorithms. IEEE Transactions on Knowledge and Data Engineering 19(11), 1479-1493 (2007)