%0 Book Section %1 smits:2005:GPTP %A Smits, Guido %A Kordon, Arthur %A Vladislavleva, Katherine %A Jordaan, Elsa %A Kotanchek, Mark %B Genetic Programming Theory and Practice III %C Ann Arbor %D 2005 %E Yu, Tina %E Riolo, Rick L. %E Worzel, Bill %I Springer %K GP Pareto Regression, Selection, Symbolic Variable algorithms, genetic programming, %P 79--92 %T Variable Selection in Industrial Datasets using Pareto Genetic Programming %V 9 %X This chapter gives an overview, based on the experience from the Dow Chemical Company, of the importance of variable selection to build robust models from industrial datasets. A quick review of variable selection schemes based on linear techniques is given. A relatively simple fitness inheritance scheme is proposed to do nonlinear sensitivity analysis that is especially effective when combined with Pareto GP. The method is applied to two industrial datasets with good results. %& 6 %@ 0-387-28110-X

@incollection{smits:2005:GPTP, abstract = {This chapter gives an overview, based on the experience from the Dow Chemical Company, of the importance of variable selection to build robust models from industrial datasets. A quick review of variable selection schemes based on linear techniques is given. A relatively simple fitness inheritance scheme is proposed to do nonlinear sensitivity analysis that is especially effective when combined with Pareto GP. The method is applied to two industrial datasets with good results.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Ann Arbor}, author = {Smits, Guido and Kordon, Arthur and Vladislavleva, Katherine and Jordaan, Elsa and Kotanchek, Mark}, biburl = {https://www.bibsonomy.org/bibtex/2a425808a20fd40fb9ee2998acee44766/brazovayeye}, booktitle = {Genetic Programming Theory and Practice {III}}, chapter = 6, editor = {Yu, Tina and Riolo, Rick L. and Worzel, Bill}, interhash = {3350251b5320155a09dab4bcfd9f8772}, intrahash = {a425808a20fd40fb9ee2998acee44766}, isbn = {0-387-28110-X}, keywords = {GP Pareto Regression, Selection, Symbolic Variable algorithms, genetic programming,}, month = {12-14 May}, notes = {part of \cite{yu:2005:GPTP} Published Jan 2006 after the workshop}, pages = {79--92}, publisher = {Springer}, series = {Genetic Programming}, size = {14 pages}, timestamp = {2008-06-19T17:51:54.000+0200}, title = {Variable Selection in Industrial Datasets using Pareto Genetic Programming}, volume = 9, year = 2005 }