An optimized hill climbing algorithm for feature subset selection: Evaluation on handwritten character recognition

Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR

Volumn , Issue , 2004, Pages 365-370

  Nunes, Carlos M ^a   De Britto Jr , Alceu S ^a,b   Kaestner, Celso A A ^a   Sabourin, Robert ^c  

^a PONTIFICAL CATHOLIC UNIVERSITY OF PARANÁ   (Brazil)

^b STATE UNIVERSITY OF PONTA GROSSA   (Brazil)

^c ÉCOLE DE TECHNOLOGIE SUPÉRIEURE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DIGIT RECOGNITION EXPERIMENT; FEATURE SUBSETS; HANDWRITTEN CHARACTER RECOGNITION; HILL-CLIMBING ALGORITHM;

ALGORITHMS; COMPUTATIONAL COMPLEXITY; DATABASE SYSTEMS; OPTIMIZATION; SET THEORY;

CHARACTER RECOGNITION;

EID: 18044399157     PISSN: 15505235     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IWFHR.2004.18     Document Type: Conference Paper

References (9)

1. Jain, A., Duin, R. P. W. and Mao, J., "Statistical pattern recognition: a review", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22(1), pp. 4-37, January 2000.
2. Boz, Olcay, "Feature subset selection by using sorted feature relevance", ICMLA International Conference on Machine Learning and Application, Las Vegas City, USA, June, pp. 147-153, 2002.
3. Molina, Luis Carlos, Belanche, Lluis and Nebot, Angela, "Feature selection algorithms: survey experimental and evaluation", IEEE International Conference on Data Mining, vol. 1, pp. 306-313, Maebashi City, Japan, December 2002.
4. Blum, Avrim L. and Langlev Pat, "Selection of relevant features and examples in machine learning", special issue Artificial Intelligence, vol. 97, n.1-2, pp. 245-271, December 1997.
5. Aha, David W. and Richard L. Bankert, "Feature selection for case-based classification of cloud types: an empirical comparison", Working Notes of the AAAI, Workshop on Case-Based Reasoning, vol. 1, pp. 106-112, 1994.
6. Raman, Baranidharan. "Enhancing inductive learning using feature and example selection", Master Thesis submitted to Texas A&M University, 67p. 2003.
7. Kohavi, Ron and John, George H., "Wrappers for feature subset selection", in Artificial Intelligence Journal, Special Issue On Relevance, vol. 97, no. 1, pp. 273-324, 1997.
8. Oliveira, L. S., Sabourin R., Bortolozzi F., and C. Y. Suen, "Feature selection using multi-objective genetic algorithms for handwritten digit recognition", Proc. International Conference on Pattern Recognition, vol. 1, pp. 568-571, Quebec City, August 2002.
9. Oliveira, L.S., Sabourin, R., Bortolozzi, F. and Suen, C.Y., "A methodology for feature selection using multi-objective genetic algorithms for handwritten digit string recognition", in the International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), vol. 17, n. 6, pp. 903-929, 2003.