%0 Conference Paper %1 iba:1999:BBBGP %A Iba, Hitoshi %B Proceedings of the Genetic and Evolutionary Computation Conference %C Orlando, Florida, USA %D 1999 %E Banzhaf, Wolfgang %E Daida, Jason %E Eiben, Agoston E. %E Garzon, Max H. %E Honavar, Vasant %E Jakiela, Mark %E Smith, Robert E. %I Morgan Kaufmann %K algorithms, classifier ensembles genetic programming, %P 1053--1060 %T Bagging, Boosting, and Bloating in Genetic Programming %U http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-407.ps %V 2 %X subpopulations %@ 1-55860-611-4

@inproceedings{iba:1999:BBBGP, abstract = {subpopulations}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Orlando, Florida, USA}, author = {Iba, Hitoshi}, biburl = {https://www.bibsonomy.org/bibtex/26cbf6b313cfc5605e10b71dc94e34b1f/brazovayeye}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Banzhaf, Wolfgang and Daida, Jason and Eiben, Agoston E. and Garzon, Max H. and Honavar, Vasant and Jakiela, Mark and Smith, Robert E.}, interhash = {351ad709a63d877b48da030ca87cf8b8}, intrahash = {6cbf6b313cfc5605e10b71dc94e34b1f}, isbn = {1-55860-611-4}, keywords = {algorithms, classifier ensembles genetic programming,}, month = {13-17 July}, notes = {GECCO-99 A joint meeting of the eighth international conference on genetic algorithms (ICGA-99) and the fourth annual genetic programming conference (GP-99) 10 Subpopulations each has its own training data (produced using the boosting or bagging methods. Best of each subpopulation has vote in final result. Do we actually need subpopulations, could not the whole algorithm be split into T entirely separate GP runs? SGPC1.1 p1054 {"}controlling the bloating effect is closely related to the performance improvement...{"} noisy cos(2x)=1-sin(x)**2, Mackey-Glass chaotic time series, 6MUX, symbolic regression, nikkei225 Description of boosting weight adjustment algorithm (p1054) seems to be wrong? p1056 BagGP, BoostGP > GP, BagGP=BoostGP But only in the case of noisy cos(2x) does difference (table 2) seem big. Mention of DSS and PADO. p1059 Says Bagging and Boosting yield lower bloat. (does not explain why) Little supporting data (Fig 5). Boosting v co-evolution}, pages = {1053--1060}, publisher = {Morgan Kaufmann}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:42:04.000+0200}, title = {Bagging, Boosting, and Bloating in Genetic Programming}, url = {http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-407.ps}, volume = 2, year = 1999 }