A novel field learning algorithm, for dual imbalance text classification

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

Volumn 3614 LNAI, Issue , 2006, Pages 39-48

  Zhuang, Ling ^a   Dai, Honghua ^a   Hang, Xiaoshu ^a  

^a DEAKIN UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; PROBLEM SOLVING; SET THEORY; TEXT PROCESSING;

FEATURE IMBALANCE; FISH-NET ALGORITHMS; TEXT CLASSIFICATION;

LEARNING ALGORITHMS;

EID: 33749057780     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11540007_6     Document Type: Conference Paper

References (7)

1. Forman, G.: A pitfall and solution in multi-class feature selection for text classification. In: Proceedings of the 21st International Conference on Machine Learning. (2004)
2. Zheng, Z., Wu, X., Srihari, R.: Feature selection for text categorization on imbalanced data. ACM SIGKDD Explorations Newsletter :Special issue on learning from imbalanced datasets 6 (2004) 80-89
3. Dai, H., Hang, X., Li, G.: Inexact field learning: An approach to induce high quality rules from low quality data. In: Proceedings of 2001 IEEE International Conference on Data Mining. (2001)
4. Ciesielski, V., Dai, H.: Fisherman: a comprehensive discovery, learning and forecasting systems. In: Proceedings of 2nd Singapore International Conference on Intelligent System. (1994) B297(1)-B297(6)
5. Dai, H., Ciesielski, V.: Learning of inexact rules by the fish-net algorithm from low quality data. In: Proceedings of the Eighth Australian Joint Artificial Intelligence Conference. (1994) 108-115
6. Witten, I.H., Frank, E.: Data mining: practical machine learning tools and techniques with Java implementations. Morgan Kaufmann (1999)
7. Joachims, T.: Making large-scale support vector machine learning practical. In B. Scholkopf, C. Burges, A.S., ed.: Advances in Kernel Methods: Support Vector Machines. MIT Press, Cambridge, MA (1998)