Discriminative vs. generative classifiers for cost sensitive learning

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

Volumn 4013 LNAI, Issue , 2006, Pages 479-490

  Drummond, Chris ^a  

^a NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; COSTS; DATA ACQUISITION;

CLASS FREQUENCIES; COST SENSITIVE LEARNING; MULTIPLE DISCRIMINATIVE CLASSIFIERS; TRADITIONAL CLASSIFICATION TASK;

LEARNING SYSTEMS;

EID: 33746064858     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11766247_41     Document Type: Conference Paper

References (16)

1. Rubinstein, Y.D., Hastie, T.: Discriminative vs informative learning. In: Knowledge Discovery and Data Mining. (1997) 49-53
2. Vapnik, V.: Statistical Learning Theory. Wlley (1998)
3. Tong, S., Koller, D.: Restricted Bayes optimal classifiers. In: Proceedings of the 17th National Conference on Artificial Intelligence. (2000) 658-664
4. Ng, A.Y., Jordan, M.: On discriminative vs. generative classifiers: A comparison of logistic regression and naive Bayes. In: Advances in Neural Information Processing Systems 14. MIT Press (2002)
5. Jaakkola, T.S., Haussler, D.: Exploiting generative models in discriminative classiers. In: Advances in Neural Information Processing Systems. MIT Press (1999) 487-493
6. Provost, F., Domingos, P.: Tree induction for probability-based ranking. Machine Learning 52 (2003)
7. Platt, J.: Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. In: Advances in Large-Margin Classifiers. MIT Press (2000) 61-74
8. Drummond, C., Holte, R.C.: Cost curves: An improved method for visualizing classifier performance. Machine Learning (In Press)
9. Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann (2005)
10. Drummond, C.: Discriminative vs. generative classifiers: An in-depth experimental comparison using cost curves, http://iit-iti.nrc-cnrc.gc.ca/ personnel/drummond_christopher_e.html (2006)
11. Blake, C.L., Merz, C.J.: UCI repository of machine learning databases, http://www.ics.uci.edu/~mlearn/MLRepository.html (1998)
12. Quinlan, J.R.: C4.5 Programs for Machine Learning. Morgan Kaufmann (1993)
13. Zadrozny, B., Elkan, C.: Transforming classifier scores into accurate multiclass probability estimates. In: Proceedings of the Eighth International Conference on Knowledge Discovery & Data Mining. (2002)
14. Rumelhart, D.E., McClelland, J.L.: Parallel distributed processing: explorations in the microstructure of cognition. MIT Press (1986)
15. Bishop, C.M.: Neural networks for pattern recognition. OUP (1996)
16. Drummond, C., Holte, R.C.: Exploiting the cost (in)sensitivity of decision tree splitting criteria. In: Proceedings of the 17th International Conference on Machine Learning. (2000) 239-246