Knowledge mining with genetic programming methods For variable selection in flavor design

Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10

Volumn , Issue , 2010, Pages 941-948

  Vladislavleva, Katya ^a   Veeramachaneni, Kalyan ^b   Burland, Matt ^c   Parcon, Jason ^c   O'Reilly, Una May ^b  

^a UNIVERSITY OF ANTWERP   (Belgium)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c Givaudan Roure Corporation   (United States)

Author keywords

Ensemble modeling; Genetic programming; Sensory science; Symbolic regression; Variable selection

Indexed keywords

DATA SETS; ENSEMBLE MODELING; KNOWLEDGE MINING; MULTIPLE MODELS; REPEATED MEASURES; SENSORY SCIENCE; SYMBOLIC REGRESSION; VARIABLE SELECTION;

COMPUTER SOFTWARE SELECTION AND EVALUATION; FLAVORS; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS;

GENETIC PROGRAMMING;

EID: 77955895438     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1830483.1830651     Document Type: Conference Paper

References (15)

1. Evolved Analytics LLC. DataModeler Release 1.0. Evolved Analytics LLC, 2010.
2. F. D. Francone, L. M. Deschaine, T. Battenhouse, andJ. J. Warren. Discrimination of unexploded ordnance from clutter using linear genetic programming. In Late Breaking Papers at the 2004 Genetic and Evolutionary Computation Conference, Seattle, Washington, USA, 26 July 2004.
3. R. J. Gilbert, R. Goodacre, B. Shann, D. B. Kell, J. Taylor, andJ. J. Rowland. Genetic programming-based variable selection for high-dimensional data. In Genetic Programming 1998: Proceedings of the Third Annual Conference, pages 109-115, Wisconsin, USA, 1998. Morgan Kaufmann.
4. M. Keijzer. Scaled symbolic regression. Genetic Programming and Evolvable Machines, 5(3):259-269, Sept. 2004.
5. M. F. Korns. Large-scale, time-constrained symbolic regression. In R. L. Riolo, T. Soule, and B. Worzel, editors, Genetic Programming Theory and Practice IV, volume 5 of Genetic and Evolutionary Computation, chapter 16, pages 299-314. Springer, Ann Arbor, May 2006.
6. J. R. Koza. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge, MA, USA, 1992.
7. J. Landry, L. D. Kosta, andT. Bernier. Discriminant feature selection by genetic programming: Towards a domain independent multi-class object detection system. Journal of Systemics, Cybernetics and Informatics., 3(1), 2006.
8. K. Neshatian, M. Zhang, andM. Johnston. Feature construction and dimension reduction using genetic programming. In Australian Conference on Artificial Intelligence, volume LNCS 4830, pages 160-170. Springer, 2007.
9. R. Poli. Genetic programming for feature detection and image segmentation. In T. C. Fogarty, editor, Evolutionary Computing, number 1143, pages 110-125. Springer-Verlag, University of Sussex, UK, 1-2 1996.
10. M. D. Schmidt andH. Lipson. Coevolution of fitness predictors. IEEE Transactions on Evolutionary Computation, 12(6):736-749, Dec. 2008.
11. J. R. Sherrah, R. E. Bogner, andA. Bouzerdoum. The evolutionary pre-processor: Automatic feature extraction for supervised classification using genetic programming. In Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 304-312, Stanford University, CA, USA, July 1997. Morgan Kaufmann.
12. G. Smits, A. Kordon, K. Vladislavleva, E. Jordaan, andM. Kotanchek. Variable selection in industrial datasets using pareto genetic programming. In T. Yu, R. L. Riolo, and B. Worzel, editors, Genetic Programming Theory and Practice III, volume 9 of Genetic Programming, chapter 6, pages 79-92. Springer, Ann Arbor, 12-14 May 2005.
13. G. Smits andM. Kotanchek. Pareto-front exploitation in symbolic regression. In U.-M. O'Reilly, T. Yu, R. L. Riolo, and B. Worzel, editors, Genetic Programming Theory and Practice II, chapter 17. Springer, Ann Arbor, 13-15 May 2004.
14. K. Veeramachaneni, K. Vladislavleva, M. Burland, J. Parcon, and U.-M. O'Reilly. Evolutionary optimization of avors. In Proceedings of GECCO, 2010.
15. J. Yu, J. Yu, A. A. Almal, S. M. Dhanasekaran, D. Ghosh, W. P. Worzel, andA. M. Chinnaiyan. Feature selection and molecular classification of cancer using genetic programming. Neoplasia, 9(4):292-303, Apr. 2007.