Naive bayes for text classification with unbalanced classes

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

Volumn 4213 LNAI, Issue , 2006, Pages 503-510

  Frank, Eibe ^a   Bouckaert, Remco R ^a,b  

^a UNIVERSITY OF WAIKATO   (New Zealand)

^b Xtal Mountain Information Technology   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; DATA PROCESSING; DATABASE SYSTEMS; PREDICTIVE CONTROL SYSTEMS; PROBLEM SOLVING;

DATA NORMALIZATION STEPS; DATA TRANSFORMATIONS; MULTINOMIAL NAIVE BAYES (MNB);

CLASSIFICATION (OF INFORMATION);

EID: 33750368009     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11871637_49     Document Type: Conference Paper

References (4)

1. Rennie, J.D., Shih, L., Teevan, J., Karger, D.R.: Tackling the poor assumptions of naive Bayes text classifiers. In: Proc Int Conf on Machine Learning. (2003) 616-623
2. Kibriya, A.M., Frank, E., Pfahringer, B., Holmes, G.: Multinomial naive Bayes for text categorization revisited. In: Proc Australian Conf on AI. (2004) 488-499
3. Han, E.H., Karypis, G.: Centroid-based document classification: Analysis and experimental results. In: Proc European Conf on Principles and Practice of Knowledge Discovery in Databases. (2000) 424-431
4. Nadeau, C., Bengio, Y.: Inference for the generalization error. Machine Learning 52(3) (2003) 239-281