Bias analysis in text classification for highly skewed data

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2005, Pages 781-784

  Tang, Lei ^a   Liu, Huan ^a  

^a Arizona State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA PROCESSING; FEATURE EXTRACTION; SUPPORT VECTOR MACHINES;

BI-NORMAL SEPARATION; BIAS ANALYSIS; INFORMATION GAIN; SKEWED DATA; TEXT CLASSIFICATION;

TEXT PROCESSING;

EID: 34548548958     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2005.34     Document Type: Conference Paper

References (6)

1. G. Batista, R. C. Prati, and M. C. Monard. A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explor. Newsl., 6(1):20-29, 2004.
2. G. Forman. An extensive empirical study of feature selection metrics for text classification. J. Mach. Learn. Res., 3:1289-1305, 2003.
3. D. Mladenic and M. Grobelnik. Feature selection for unbalanced class distribution and naive bayes. In Proc. ICML, pages 258-267. Morgan Kaufmann Publishers Inc., 1999.
4. L. Tang and H. Liu. Bias analysis in text classification for highly skewed data. Technical Report TR-06-005, Arizona State University, 2005.
5. G. Weiss and F. Provost. Learning when training data are costly: The effect of class distribution on tree induction. JAIR, 19:315-354, 2003.
6. Y. Yang and J. O. Pedersen. A comparative study on feature selection in text categorization. In Proc. ICML, pages 412-420. Morgan Kaufmann Publishers Inc., 1997.